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.

No description available.

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.

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

No description available.

Predictive decision theory explains how humans should make decisions in practice given that they are not always perfect rational decision makers. Based on the prescriptive decision theory, this study addresses criticism of universal decision making models for supplier selections which have the notion of being used uniquely in all types of supplier choice situations. Issues raised are whether this performance is correct and how a dynamic decision-making model could create a more customized decision-making model which does not add much responsibility to the decision maker's judgment. A case study at Logosol, a small industrial company identifies by process mapping a complex supplier selection process consisting of three steps; prototype creation, null-series and production, based on test manufacturing. The supplier selection process is used as the basis for the creation of a dynamic decision making model. Dynamic decision-making models have the basic principle of learning from a decision and using that information in the next decision, which is considered useful in the business case as they not only use test manufacturing for product testing but also for collecting information about the supplier. Finally, the created dynamic decision model shows that universal decision-making models cannot be used in many complex supplier selection processes involving a plurality of steps. The model must be adapted to the company's individual process, however the identification method or some parts of the model used in this study may be used to create a dynamic decision model for other companies or organizations. / Preskriptiv beslutsteori säger hur människan borde fatta beslut i praktiken givet att de inte alltid är perfekt rationella beslutsfattare. Utifrån den preskriptiva beslutsteorin riktas i denna studie kritik mot universella beslutsmodeller för leverantörsval vilka har föreställningen om sig att användas kunna användas universellt i alla olika typer av leverantörsvalssituationer. Frågeställningar som väckts är om denna föreställning stämmer, samt hur en dynamisk beslutsmodell skulle kunna skapa en mer anpassad beslutsmodell vilken inte lägger lite mycket ansvar på beslutsfattarens omdöme. Genom en fallstudie hos Logosol ett litet industriföretag identifieras med hjälp av processkartläggning en komplex leverantörsvalsprocess innefattande tre steg; prototypskapande, nollserieskapande samt produktion utifrån testtillverkning. Fallföretagets leverantörsvalsprocess används som grund för skapande av en dynamisk beslutsmodell. Dynamiska beslutsmodeller har den grundläggande principen att medta lärdom från ett beslut in i nästa, vilket anses användbart för fallföretagets leverantörsvalsprocess då dom inte bara använder testtillverkning för test av produkt utan även för insamling av information om leverantören. Studien visar att föreställningen stämmer, den skapade dynamiska beslutsmodellen visar att universella beslutsmodeller inte är särskilt användbara i många komplexa leverantörsvalsprocesser innefattande ett flertal steg. Modellen måste anpassas för företagets individuella process, dock kan identifieringsmetoden eller vissa delar av modellen som använts i denna studie möjligtvis användas för att skapa en dynamisk beslutsmodell för andra företag eller organisationer.

This thesis focuses on decision support for regional LTL carriers. The basic operating characteristics of regional LTL carriers are similar to those of national LTL carriers, i.e., they operate linehaul networks with satellites, breakbulks, and relays to consolidate freight so as to be able to cost-effectively serve their customers. However, there are also key differences. Most importantly, because the area covered by a regional carrier is smaller, a regional carrier handles less freight (sometimes significantly less) and therefore typically has fewer consolidation opportunities, which results in higher handling and transportation costs per unit of freight. Consequently, competing with national carriers on price is difficult. Therefore, to gain or maintain market share, regional carriers have to provide better service. To be able to provide better service, regional carriers have to be more dynamic, e.g., they have to be able to deviate from their load plan when appropriate, which creates challenges for decision makers. Regional carriers deliver about 60% of their shipments within a day and almost all of their shipments within two days. Furthermore, most drivers get back to their domicile at the end of each day. Therefore, the focus of the thesis is the development of effective and efficient decision models supporting daily operations of regional LTL carriers which provide excellent service at low cost. This thesis presents an effective solution approach based on two optimization models: a dynamic load planning model and a driver assignment model. The dynamic load planning model consists of two parts: an integer program to generate the best paths for daily origin-destination freight volumes and an integer program to pack freight into trailers and trailers into loads, and to determine dispatch times for these loads. Techniques to efficiently solve these integer program solution are discussed in detail. The driver assignment model is solved in multiple stages, each stage requiring the solution of a set packing models in which columns represent driver duties. Each stages determines admissible driver duties. The quality and efficiency of the solution approach are demonstrated through a computational study with real-life data from one of the largest regional LTL carriers in the country. An important "technique" for reducing driver requirements is the use of meet-and-turn operations. A basic meet-and-turn operation involves two drivers meeting at a location in between terminals and exchange trucks. A parking lot or a rest area suffices as a meet-and-turn location. This ensures that drivers return to the terminal where they started. More sophisticated meet-and-turn operations also exist, often called drop and hook operations. In this case, drivers do not exchange trucks, but one of their trailers. The motivation in this case is not to get drivers back to their domicile, but to reduce load- miles. The thesis presents analytical results quantifying the maximum benefits of using meet and turn operations and optimization techniques for identifying profitable meet-and-turn opportunities.

The modern business environment requires managers to make decisions in a dynamic and uncertain world. In the current study, experimenters investigated the effects of a brief training aimed at improving dynamic decision making (DDM) skills on individual performance in a virtual DDM task. During the training, experimenters explained the DDM process, stressed the importance of self-reflection in DDM, and provided 3 selfreflective questions to guide participants during the task. Additionally, experimenters explored whether participants low or high in self-reflection would perform better in the task and whether participants low or high in self-reflection would benefit more from the training. Participants were 68 graduate business students. They individually managed a computer-simulated chocolate production company called CHOCO FINE and answered surveys to assess self-reflection and demographics. Results showed that students trained in DDM made decisions leading to better management performance in CHOCO FINE compared to untrained students. Self-reflection scores also predicted performance in this virtual business, and participants low in self-reflection benefitted the most from training. Organizations could use DDM training to establish and promote a culture that values selfreflective decision making.