Master of Science / Department of Psychological Sciences / Michael E. Young / Although risky decision-making tasks present some a priori risk (i.e., base-rate), decision makers often have an opportunity to modify this level of risk through their behaviors. Broadly speaking, risk can be modified by assigning additional resources to an ongoing task or by engaging in specific risk-mitigation strategies before or after the risky decision is made. The modification of risk requires ongoing awareness of task demands, resource constraints, and risk-mitigation strategies that can be used to adapt behavior over time. This thesis explores risk modification that occurs during difficult tasks. Difficult tasks hold greater risks because they fall at the edge of the decision maker’s abilities and are likely to require a greater number of resources to overcome. As resources are engaged they become unavailable for other tasks or strategies to cope with changing task demands. I studied how individuals monitor risks and develop risk mitigation strategies using a videogame task designed to mirror contingencies that would be encountered in the real world. Results from two experiments that involve this task suggest that decision-makers adequately monitor and develop active strategies for dealing with risks. These strategies change over time and vary as a function of task difficulty and experience.

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In the first chapter, I analyze the question that whether the elasticity of intertemporal substitution or risk aversion is more important determinant of precautionary savings. This is an important question since a significant fraction of the capital accumulation is due to precautionary savings according to studies. Thus, knowing the important determinant of precautionary savings will be helpful to understand the capital accumulation mechanism. I look into the effects of the elasticity of intertemporal substitution and risk aversion on precautionary savings separately by performing simulations in order to obtain numerical results. I find that the elasticity of intertemporal substitution is more important determinant than risk aversion. In the second chapter, I study the impact of the introduction of futures trading on the volatility of the underlying spot market for Turkish Istanbul Stock Exchange (ISE).The economic literature intensified the debate on the negative or positive impact of futures trading on the stock market volatility. Although there are empirical studies for different countries with mixed results, most of them focus on developed countries. There are a few empirical researches on emerging markets. Analyzing the data, following results are obtained for ISE. First, the results suggest that the introduction of futures trading has decreased the volatility of ISE. Second, the results show that futures trading increases the speed at which information is impounded into spot market prices. Third, the asymmetric responses of volatility to the arrival of news for ISE have increased after the introduction of futures trading. In the third chapter, I investigate the presence of calendar anomalies in ISE by using GARCH models. The presence of calendar anomalies and their persistence presence since their first discovery still remains a puzzle to be solved. On the other hand, there are some claims that general anomalies are much less pronounced after they became known to the public. Most of the studies have examined the developed financial markets. However, it is important to test the calendar effects in data sets that are different from those in which they are originally discovered and so ISE is a good case to test the calendar effects for a developing country. / text

This thesis focuses on the cooperative and communicative aspects of control over dynamic situations such as emergency management and military operations. Taking a stance in Cognitive Systems Engineering, Decision making and Communication studies, the role of information systems as tools for communication in dynamic situations is examined. Three research questions are examined; 1 ) How new forms of information technology affects joint control tasks in dynamic situations, and how/if microworld simulations can be used to investigate this. 2 ) What the characteristics of actual use of information systems for joint control are in dynamic situations? 3 ) What the pre-requisites are for efficient communication in joint control tasks and especially in dynamic, high-risk situations? Four papers are included. A study performed with a microworld simulation involving military officers as participants is presented, and the method of using microworlds for investigating the effects of new technology is discussed. Field observations from an emergency call centre are used to exemplify how information systems actually are used in a cooperative task. An interview study with military officers from a UN-mission describes the social aspects of human-human communication in a dynamic, high risk environment. Finally, an elaborated perspective on the role of information systems as tools for communication, and especially the relation between the social, organisational and technical layers of a joint control activity is presented.

The mobile operators face the problem that the users how to transfer from 2G to 3G as well as telecommunication policy has been opened by government¡F mobile number protablility¡Bthe new 3G competitor¡¦s entry as to result in unexpected revenue in Taiwan. However, the new 3G competitor¡As entry with the great impact on TWM, then the actual utility is lower of TWM. The study is exploring for ¡yThe effect on subscribers diffusion 3G mobile optrator dynamic decision effect on¡z, because the property of problem is high order¡Bnonlinear¡Btime delay, the traditional approach lacking of quantifying basis such as Case Study which cannot simulate the consequence of feasible policy. It cannot estimate what becomes of the solution, thus apt to making wrong decision. Others mathematics approachs cannot explain the dynamic essence of the practical problem. All these approaches are linear and static as linear programing¡BQueuing Theory¡B Monte Carlo Simulation that cannot solve the high order¡Bdynamic problem. These approaches are no usefulness in solving practical management problem. However, System Dynamics is able to solve the dynamic complexity problem that trough the steps of problem description¡B boundary definition¡Bsystem model constructing¡B model testing and simulation to understand the structure and behavior of problem, moreover, to do policy design and evaluation. This study is as system dynamics approach on the foundation of BASS diffusion model and constructing model upon the 3G adoption critical factor in the viewpoint of Theory of Planed Behavior. The objective of study is to construct the diffusion model of TWM subscribers upon system dynamics, then to seek the leading loop and high leverage of behavior through scenario analysis for consultation in policy design. The conclusion of study as following¡]1¡^if the operators take high allowance of GSM handset bundling contract sales, will trun up¡yThe self-limit to growing¡z. When the price competition between operators in the market, the policy will cause that TWM 3G actual subscribers are lower. The best revenue policy is to shorten GSM contract duration by handset price or ceasing GSM bundling contract sales schedule to be advanced.¡]2¡^If all the operators do not do the competition in price aggressively in oligopoly, the relationship between competitors will result in¡yThe rich more rich and the poor more poor¡z. The best revenue policy for operator is the tariff shall be divided into different stages to co-operate with network load and to acquire high data usage subscribers for the goal. It shall reduce the threshold of customer entry for the sake of increasing subscribers in the middle stage. There is an obvious discrenpancy between the best policy in simulation and operator taking. ¡]3¡^If the operators attempt to shorten the timetable of subscribers from GSM transfer to 3G as to shorten GSM contract duration, the network constructing policy should do dynamic policy co-operation with the leading indicator of subscribers diffusion. The scenario simulation upon system dynamics that the counter-intuitive phenomenon often contrasts to the operator¡¦s preconception, avoiding to the confined thinking in policy design.

Att utveckla och bibehålla situation awareness (SA) är en av de mest kritiska utmaningar i en stab i dagens konflikter. Det får avgörande betydelse för utgången av en konflikt. Om SA hanteras eller förstås felaktigt kan det leda till ökat mänskligt lidande i konfliktområden och förluster av människoliv. Det ökande internationella samarbetet gör att planeringsofficeren förutsätts kunna hantera flera olika processer. Syftet med uppsatsen var att jämföra och belysa skillnader hur SA skapas inom olika planeringsprocesser, samt vad försvårar utväxlingen av SA mellan processerna. Detta återspeglas i form av likheter och skillnader mellan planeringsmodellerna SPL, MCPP och COPD. Resultatet visar att det fanns stor likhet mellan processerna men det fanns också avgörande skillnader. I SA nivå 1 fanns en diskrepans mellan begreppen Centre of Gravity, caveats och gender. I SA nivå 2 skiljer bearbetningsprocesserna mellan planeringsmodellerna. I SA nivå 3 fanns den största och mest avgörande skillnaden där det kan konstateras att planeringsprocesserna inte utgår från samma byggstenar när det gäller att bygga planen. Medvetenhet och insikt för de olika planeringsprocessernas särart minskar risken för missförstånd.

This thesis deals with the multi-stage stochastic programming problems. In the first part, there are introduced two-stage and multi-stage stochastic programming problems. Next, two methods how to generate scenarios are described in detail - the moment method and paths-based methods. The second chapter describes the flower-girl problem, its various formulations and other extensions using ro- bustness and endogenous randomness. The practical part follows, where several different formulations of the flower-girl problem are solved. First, the problem when the florist sells roses with an unlimited life for one week is solved. Then this problem is reformulated as a two-stage problem and the results are compared. Then a formulation with a limited rose life of 2 days is presented. The greatest attention is paid to the problem with a limited rose life of 4 days - the basic formulation of the problem and several extended formulations are solved. 1

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24736号 / 情博第824号 / 新制||情||138(附属図書館) / 京都大学大学院情報学研究科社会情報学専攻 / (主査)教授 多々納 裕一, 教授 畑山 満則, 教授 森 信人 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Making good predictions is a critical feature of decision making in situations such as investing and predicting the spread of diseases. Past literature indicates that people use recent and longer-term trends while making predictions. Nonetheless, less is known about how these factors affect how well people make predictions and the timing of their predictions. Further, identifying factors underlying predictive judgments could be an important behavioral factor in manic-depression, anxiety, substance use, age effects, and understanding how income inequality affects decision making. To understand how people make predictive judgments, we conducted two experiments. In Experiment 1, we used an investment task where participants had to predict the future price of a stock based on an exponential trend of information. We found that participants generally had lower earnings with steeper exponential trends (e.g. slower starting) and delayed their decisions to sell bad stocks with steeper trends. We extended these results in Experiment 2 with an updated task with exponential and inverse exponential trends. Overall, our results suggested that people delayed longer to make their prediction with slower starting exponential trends compared to faster starting inverse exponential trends and delayed their predictions longer with more linear trends compared to more trend trends. When deciding how long to explore, participants incorporated both the average trend and recent trend, though they shifted their responses depending on the overall functional form. These choices were ultimately biased to be optimistic or pessimistic based on whether the trend started fast or slow, respectively. Additionally, we found that participants who self-reported taking more gambling risk and depressive symptoms had a greater tendency to stay with faster starting trends and to leave with slower starting trends, suggesting they were even more optimistic given initially fast starting trends. Results pointing to an optimism bias based on the trend in information available to the participant could suggest that an aspect of sunk-cost fallacy is due to errors in predicting the likelihood of future success based on past information. Our findings help understand the dynamics of how people make predictive judgments over time and could inform future research into the mechanisms people use for prospective decision making. Additionally, future research and potential interventions could account for biases in how people perceive past trends to minimize harmful effects of sunk-cost fallacy when making predictions. / Psychology

Medical decision problems are extremely complex owing to their dynamic nature, large number of variable factors, and the associated uncertainty. Decision support technology entered the medical field long after other areas such as the airline industry and the manufacturing industry. Yet, it is rapidly becoming an indispensable tool in medical decision making problems including the class of sequential decision problems. In these problems, physicians decide on a treatment plan that optimizes a benefit measure such as the treatment cost, and the quality of life of the patient. The last decade saw the emergence of many decision support applications in medicine. However, the existing models have limited applications to decision problems with very few states and actions. An urgent need is being felt by the medical research community to expand the applications to more complex dynamic problems with large state and action spaces. This thesis proposes a methodology which models the class of sequential medical decision problems as a Markov decision process, and solves the model using a simulation based reinforcement learning (RL) algorithm. Such a methodology is capable of obtaining near optimal treatment strategies for problems with large state and action spaces. This methodology overcomes, to a large extent, the computational complexity of the value-iteration and policy-iteration algorithms of dynamic programming. An average reward reinforcement-learning algorithm is developed. The algorithm is applied on a sample problem of treating hereditary spherocytosis. The application demonstrates the ability of the proposed methodology to obtain effective treatment strategies for sequential medical decision problems.