This dissertation consists of three research papers on Preference models of decision making, all of which adopt an axiomatic approach in which preference conditions are studied so that the models in this dissertation can be verified by checking their conditions at the behavioral level. The first paper “Utility Functions Representing Preference over Interdependent Attributes” studies the problem of how to assess a two attribute utility function when the attributes are interdependent. We consider a situation where the risk aversion on one attribute could be influenced by the level of the other attribute in a two attribute decision making problem. In this case, the multilinear utility model—and its special cases the additive and multiplicative forms—cannot be applied to assess a subject’s preference because utility independence does not hold. We propose a family of preference conditions called nth degree discrete distribution independence that can accommodate a variety of dependencies among two attributes. The special case of second degree discrete distribution independence is equivalent to the utility independence condition. Third degree discrete distribution independence leads to a decomposition formula that contains many other decomposition formulas in the existing literature as special cases. As the decompositions proposed in this research is more general than many existing ones, the study provides a model of preference that has potential to be used for assessing utility functions more accurately and with relatively little additional effort. The second paper “On the Axiomatization of the Satiation and Habit Formation Utility Models” studies the axiomatic foundations of the discounted utility model that incorporates both satiation and habit formation in temporal decision. We propose a preference condition called shifted difference independence to axiomatize a general habit formation and satiation model (GHS). This model allows for a general habit formation and satiation function that contains many functional forms in the literature as special cases. Since the GHS model can be reduced to either a general satiation model (GSa) or a general habit formation model (GHa), our theory also provides approaches to axiomatize both the GSa model and the GHa model. Furthermore, by adding extra preference conditions into our axiomatization framework, we obtain a GHS model with a linear habit formation function and a recursively defined linear satiation function. In the third paper “Hope, Dread, Disappointment, and Elation from Anticipation in Decision Making”, we propose a model to incorporate both anticipation and disappointment into decision making, where we define hope as anticipating a gain and dread as anticipating a loss. In this model, the anticipation for a lottery is a subjectively chosen outcome for a lottery that influences the decision maker’s reference point. The decision maker experiences elation or disappointment when she compares the received outcome with the anticipated outcome. This model captures the trade-off between a utility gain from higher anticipation and a utility loss from higher disappointment. We show that our model contains some existing decision models as its special cases, including disappointment models. We also use our model to explore how a person’s attitude toward the future, either optimistic or pessimistic, could mediate the wealth effect on her risk attitude. Finally, we show that our model can be applied to explain the coexistence of a demand for gambling and insurance and provides unique insights into portfolio choice and advertising decision problems. / text

Yes / Modern aeronautical telecommunication networks (ATN) make use of different simultaneous datalinks to deliver robust, secure and efficient ATN services. This paper proposes a Multiple Attribute Decision Making based optimal datalink selection algorithm which considers different attributes including safety, QoS, costs and user/operator preferences. An intelligent TRigger-based aUtomatic Subjective weighTing (i-TRUST) method is also proposed for computing subjective weights necessary to provide user flexibility. Simulation results demonstrate that the proposed algorithm significantly improves the performance of the ATN system. / Innovate U.K. Project SINCBAC-Secure Integrated Network Communications for Broadband and ATM Connectivity: Application number 18650-134196.

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Doctor of Philosophy / Department of Industrial and Manufacturing Systems Engineering / Bradley Kramer / This research shows that industry and company related performance indicators enhance the business valuation process by providing a broader, more encompassing view of overall corporate health and a better understanding of improvement opportunity areas within a company. To incorporate performance indicators in the business valuation process, new methodologies are required to integrate the non-financial and soft data with the typical financial information used in business valuation. This requires a “re-think” of the standard business valuation process and the exploration and application of other methods and analytical techniques. The results of this research are the definition of a problem type and the development of a new business valuation process. The problem structure has as inputs industry specific performance metrics grouped into three primary areas Production Processes, Products/Services and Marketability and Management, a fuzzy logic model with fuzzy and approximate relationships between performance metrics and financial information and crisp financial information as output. The framework for a fuzzy logic model was developed and is used to approximate relationships and model a non-linear environment. The resulting crisp financial information is then input and integrated into the traditional business valuation process. The process was demonstrated with an example production company and with data from two regional airlines. A step-by-step example of the process was provided using the production company example to demonstrate how the results are generated and integrated with DCF business valuation. Heuristics to identify areas to improve company performance were described. Two regional airlines, individually and combined, were tested with actual data using the original fuzzy logic model structure and then the original fuzzy logic model structure was revised and new results generated. Tuning the model showed an improvement in the business valuation process performance. The benefits from this research include the definition of a new class of problems and a process to solve problems of this nature. The insights gained from this research can be applied in major disciplines such as accounting, business and finance, engineering and decision theory.

The problems, associated with sensitivity of quantitative multiattribute decision-making methods to the initial data and the reliability of the decision obtained by using these methods, are considered in the presented dissertaition. The methods discussed are applied to solving decision-making problems, consisting in the selection of one alternative out of the available several options, when a decision-making person seeks to achieve a number of aims, rather than a single aim, and the alternatives are evaluated based on a set of attribute, which may be conflicting. The research object is sensitivity of the popular quantitative multiattribute decision-making methods: TOPSIS, SAW and COPRAS to the initial data errors. The initial data inaccuracy may be caused by the errors made by a person, entering the data. The estimates of the alternatives may have some errors, which are not taken into account, when the considered methods are used with these data. The analysis of the related works has shown that there are methods for evaluating sensitivity with respect to one attribute, based on varying the significance values, such as the method of the most critical criterion (Triantaphyllou 2000) and to many attributes - Tornado diagram. However, these methods do not show either the errors of solution results or the reliability level of the result obtained. The main aim of the dissertation is the evaluation of the stochastic nature of multiattribute decision-making methods, based on... [to full text] / Disertacijoje nagrinėjamas kiekybinių daugiatikslių sprendimo priėmimo metodų jautrumas ir juos taikant gautų sprendimų patikimumas. Daugiatiksliai sprendimo priėmimo metodai taikomi sprendimo priėmimo uždaviniuose, renkantis vieną alternatyvą iš keleto galimų, kai sprendimą priimantis asmuo siekia ne vieno, o kelių tikslų, o alternatyvos vertinamos pagal daugelį efektyvumo rodiklių, kurie gali būti tarpusavyje prieštaraujantys (pvz. kainos ir naudos rodikliai). Pagrindinis tyrimo objektas yra metodų TOPSIS, SAW ir COPRAS jautrumas pradinių duomenų netikslumams. Duomenų netikslumai galimi dėl pradinių duomenų reikšmes nustatančio asmens padarytų klaidų. Tokiu atveju, kai taikant minėtus metodus, alternatyvų vertinimui naudojami pradiniais duomenys turintys tam tikras paklaidas, alternatyvų vertinimai gali būti su paklaidomis, kurios, taikant šiuos metodus, nebėra vertinamos. Išanalizavus susijusius darbus, nustatyta, jog yra metodų, skirtų vertinti sprendimo jautrumą vieno rodiklio atžvilgiu, keičiant reikšmingumo reikšmes, tai - kritiškiausio kriterijaus metodas (Triantaphyllou 2000) ir daugelio rodiklių atžvilgiu - Tornado diagrama. Tačiau šie metodai nepateikia nei sprendimo rezultatų paklaidų, nei rezultato patikimumo laipsnio. Pagrindinis disertacijos tikslas – įvertinti daugiatikslių, kiekybiniais matavimais pagrįstų sprendimo priėmimo metodų stochastiką. Sukurtų metodų taikymo sritis – sprendimo paramos sistemų projektavimas, sprendimų patikimumo ir sprendimų priėmimo... [toliau žr. visą tekstą]

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