Despite the fact that unguided decision making might lead to inefficient and nonoptimal decisions, decisions made at organizational levels seldom utilise decisionanalytical tools. Several gaps between the decision-makers and the computer baseddecision tools exist, and a main problem in managerial decision-making involves the lack of information and precise objective data, i.e. uncertainty and imprecision may be inherent in the decision situation. We believe that this problem might be overcome by providing computer based decision tools capable of handling the uncertainty inherent in real-life decision-making. At present, nearly all decision analytic software is only able to handle precise input, and no known software is capable of handling full scale imprecision, i.e. imprecise probabilities, values and weights, in the form of interval and comparative statements. There are, however, some theories which are able to handle some kind of uncertainty, and which deal with computational and implementational issues, but if they are never actually operationalised, they are of little real use for a decision-maker. Therefore, a natural question is how a reasonable decision analytical framework can be built based on prevailing interval methods, thus dealing with the problems of uncertain and imprecise input? Further, will the interval approach actually prove useful? The framework presented herein handles theoretical foundations for, and implementations of, imprecise multi-level trees, multi-criteria, risk analysis, together with several different evaluation options. The framework supports interval probabilities, values, and criteria weights, as well as comparative statements, also allowing for mixing probabilistic and multi-criteria decisions. The framework has also been field tested in a number of studies, proving the usefulness of the interval approach.

This thesis studies seven strategic decisions made in the family-owned forestry company Robertsfors AB, in Northern Sweden. During the present century Ro­bertsfors AB has developed from a patriarchally concern controlled into a capi­talistic industrial company. This also meant a radical change in the decision­making process. Two factors were decisive in this process: the managing direc­tor's values, and altered power relationships both within the company and exter­nally in relation to e g state and municipal authorities and labour market organi­zations. The patriarchal Seth M Kempe, managing director 1897-1927, placed greater value on the company's independence than on profitability, and he personally, after discussions with the production manager, made the strategic decisions to build a sulphite mill in 1902 and not to build a sulphate mill in 1918. He also had no confidence in outside experts. Maximum profits on paid up capital, quick decisions and delegation of re­sponsibility were the marks of the years 1928-1947, when Seth M Kempe's son Erik was managing director. The strategic decision to close down the sawmill in 1935 was made by the company board, while he himself made the decisions early in the 1940's to produce sulphite alcohol and to establish an impregnation works, and finally to close down the sulphite mill in 1948. Responsibility for the community and the company's work force increased in importance during the years 1948-1968, when Erik's brother Ragnar was man­aging director. Now the board once again had real power. Decision-making was based on negotiation and compromise between management, the board, union organizations and state authorities — which is reflected in the strategic decision of 1967 to rebuild the foundry. / digitalisering@umu

The study was designed with a dual purpose. First, the study was designed to develop and assess a systematic decision making procedural 'model which would aid in the resolution of critical issues. Second, the purpose of the study was to assess the decision making procedures of the school's chief executive officer when dealing with critical issues. The study was conducted by interviewing ten chief executive officers of Indiana school corporations. The data generated was reported in narrative and table form. The data was used to assess the developed model for comprehensiveness and adaptability and to assess the decision making procedures of chief executive officers for comprehensiveness and systematization.The findings reported herein were based on the evaluation and analysis of the data reported by public school chief executive officers and a review of related research.1. The Decision Support System model was found to be comprehensive and provided a thorough description of the processes needed by the chief executive officer in the decision making processes.2. In all cases, the Decision Support System model processes adapted to the processes of the chief executive officer.3. The chief executive officers selected and analyzed a limited amount of data to support the identification of impacts, options, and alternatives in the decision making process.4. The chief executive officers identified a limited number of impacts, options, and alternatives in the decision making process.5. The process of decision making by the chief executive officers was arranged in a form which was not consistently orderly, methodical, or well organized.6. The data in the table has shown that twenty-four of thirty-eight identified critical educational issues concerned financial problems.7. Eighty percent of the interviewed chief executive officers utilized the trade-off processes of the Decision Support System model as the option for the solution of the 8. The trade-off processes of eighty percent of the chief executive officers utilized the option of exchanging qualitative resources for quantitative resources or deleted qualitative resources in the absence of adequate funds.9. The trade-off processes of eighty percent of the chief executive officers resulted in problems involving attitudes and motivation.

En lagändring har gjorts i Sverige vars syfte är att små och medelstora företag har frivillig revision om de ligger under eller endast uppfyller ett av följande tre gränsvärden: (1) 3 miljoner kronor i nettoomsättning, (2) 1,5 miljoner kronor i balansomslutning eller (3) fler än tre anställda. Eftersom lagändringen är relativt ny, medför det att företag i dagsläget precis har avslutat eller är inne i en beslutsprocess angående den frivilliga revisionen. Beslutsfattande är något som ständigt pågår i alla former av organiserad mänsklig verksamhet och dagligen förekommer det i alla organisationer ett beslutsfattande både när det gäller rutinfrågor till mer komplexa beslut. Genom mänsklighetens historia har människan strävat efter att få kontroll över resultaten av sina beslut, öka förutsägbarheten samt minska riskerna. När beslut fattas i företag måste även hänsyn tas till en rad förhållanden som är direkt kopplat till den organisatoriska kontexten för handlandet. Syftet med denna uppsats är att undersöka hur och på vilka grunder företagen har fattat beslut vid valet av att anlita en revisor eller inte, samt analysera beslutsprocessen ur ett beslutsteoretiskt perspektiv. Följande problemformulering ligger till grund för denna studie: Vad kännetecknar ett företag som anser sig ha behov av revision trots att kravet på revision inte är tvingande? På vilka grunder är beslutet fattat? Undersökningen ska bidra till en djupare kunskap och förståelse om hur besluten fattats och hur beslutsprocessen gått till. Studien har en kvalitativ forskningsansats och bygger på telefonintervjuer med ett antal företag som står inför beslutet att välja mellan att anlita en revisor eller inte. I studien framkom det inga specifika kännetecken på de företag som ansåg att de hade behov av revision trots att kravet på revision inte längre är tvingande. Dock ansåg majoriteten att kostnaden för revision var mer värt än tiden det krävs för att kontinuerligt vara uppdaterad inom lagar, regler och praxis. Resultatet av undersökningen visar att den trygghet som revisionen ger är avgörande vid valet att behålla revisorn, eftersom den skapar bättre trovärdighet åt företaget inför kreditgivare och andra intressenter. Flertalet av respondenterna har gjort ett försök att agera och tänka rationellt då de beslutat efter vad de ansåg vara bäst för företagen. Studien visar även att respondenterna som var i en pågående beslutsprocess valde att rådfråga personer med kunskap om problemet för att därefter fatta ett kollektivt beslut. En sammanställning hur undersökningen kan se ut när alla respondenterna är klara med besluten tyder på ett resultat där 85 procent av deltagarna valt att behålla revision, 10 procent som väljer bort revision samt 5 procent av respondenterna som inte vet vilket beslut de ska fatta. / There has been a change in the law that allows small and medium-sized companies in Sweden to have voluntary audit if they are below or only exceed one of the following three limits: (1) 3 million in net sales, (2) 1, 5 million in total assets or (3) more than three employees. Since the change in the law about voluntary audit is relatively new, many companies are either in the middle of their decision-making process or have just made a decision. The process of making decision is a continuous process that every company faces every day, which regards every level of the organization. The main purpose of this paper is to analyze how and on what basis the companies have made a decision regarding the voluntary audit. The study will contribute to a deeper knowledge and understanding of how decisions are taken, in general, and how this particular decision about audit has been made. The questions this study aims to examine is: What characterizes a company that believes that they need an audit?  What basis is the decision made on?  The study has not shown any common and clear characteristics of the companies that decided that they need audit, however the majority of the researched companies thought that the cost of the audit was worth more than the time the organization needed to be updated on the new laws, rules and practices. The results of the research have shown that the safety audit gives is the most important factor when deciding whether to keep auditor or not. The reason for this is the fact that audit adds credibility and reliability in front of their creditors and other stakeholders.

Consumer decision behavior has been an interesting research topic for researchers and marketing people. While E-Commerce websites and online self-service are becoming more and more popular, it is important to understand how to support consumer in their online shopping decision process. The purpose of this research is to understand how consumer¡¦s decision behavior would be influenced in online shopping environment, when facing different product price and complexity, and discover the personal factors that might influence it¡¦s decision behavior. The result of our research showed that product complexity has significant influence on consumer¡¦s decision behavior. When product complexity become higher, the effort and time for a consumer to complete a purchase decision will also become higher. When consumer is more familiar with the product, more involve with the product, or have higher computer self-efficacy, consumer will use much harder decision tools then usual. But our result also showed that product price has no influence on consumer¡¦s decision behavior, this might be that in our experiment, consumers don¡¦t really have to pay for the product, so the influence of product price has no effect on consumer. From our result we can know that for different product complexity and consumer will result in different decision behavior. In the future, online shopping store can provide different decision tools for different consumer when facing different products, to help consumer make better decision.

The English online auction creates great business opportunities. However, it¡¦s different from traditional English auction in long bidding time, wide area, high risk, massive information, and low switching cost. It makes bidders easy to search information of the goods but difficult to win the auction. The bidders' transaction cost structure has changed from information phase to agreement phase. So, the bidders need more precise supporting tools to help them make decisions. The aim of this research is to investigate two-person optimal bidding strategies under three dimensions of the decision space: the sequence decision (bid firstly or later), the bid decision (bid or quit), and the jump decision (minimum increase or jump bid). It is assumed that there are two bidders competing in one auction. Variables associated with the auction system include the floor price and the minimum increase. Variables associated with the bidders include the private value of the bidding object, and the cost of bid per turn. Strategies were evaluated based on the following criteria: who wins, how many turns to win the bid, the deal price, the utility of the winner and the loser, the probability of winning, and the expected utility. The results indicate that every strategy has its advantages and disadvantages under certain conditions. This research provides guiding rules for the bidders to choose a better strategy.

This thesis work describes the formulation of a Bayesian approach along with new tools to systematically reduce uncertainty in Research&Development (R&D) alternatives. During the initial stages of R&D many alternatives are considered and high uncertainty exists for all the alternatives. The ideal approach in addressing the many R&D alternatives is to find the one alternative which is stochastically dominant i.e. the alternative which is better in all possible scenarios of uncertainty. Often a stochastically dominant alternative does not exist. This leaves the R&D manager with two alternatives, either to make a selection based on user defined utility function or to gather more information in order to reduce uncertainty in the various alternatives. From the decision makers perspective the second alternative has more intrinsic value, since reduction of uncertainty will improve the confidence in the selection and further reduce the high downside risk involved with the decisions made under high uncertainty. The motivation for this work is derived from our preliminary work on the evaluation of biorefiney alternatives, which brought into limelight the key challenges and opportunities in the evaluation of R&D alternatives. The primary challenge in the evaluation of many R&D alternatives was the presence of uncertainty in the many unit operations within each and every alternative. Additionally, limited or non-existent experimental data made it infeasible to quantify the uncertainty and lead to inability to develop an even simple systematic strategy to reduce it. Moreover, even if the uncertainty could be quantified, the traditional approaches (scenario analysis or stochastic analysis), lacked the ability to evaluate the key group of uncertainty contributors. Lastly, the traditional design of experiment approaches focus towards reduction in uncertainty in the parameter estimates of the model, whereas what is required is a design of experiment approach which focuses on the decision (selection of the key alternative). In order to tackle all the above mentioned challenges a Bayesian framework along with two new tools is proposed. The Bayesian framework consists of three main steps: a. Quantification of uncertainty b. Evaluation of key uncertainty contributors c. Design of experiment strategies, focussed on decision making rather than the traditional parameter uncertainty reduction To quantify technical uncertainty using expert knowledge, existing elicitation methods in the literature (outside chemical engineering domain) are used. To illustrate the importance of quantifying technical uncertainty, a bio-refinery case study is considered. The case study is an alternative for producing ethanol as a value added product in a Kraft mill producing pulp from softwood. To produce ethanol, a hot water pre-extraction of hemi-cellulose is considered, prior to the pulping stage. Using this case study, the methodology to quantify technical uncertainty using experts' knowledge is demonstrated. To limit the cost of R&D investment for selection or rejection of an R&D alternative, it is essential to evaluate the key uncertainty contributors. Global sensitivity analysis (GSA) is a tool which can be used to evaluate the key uncertainties. But quite often global sensitivity analysis fails to differentiate between the uncertainties and assigns them equal global sensitivity index. To counter this failing of GSA, a new method conditional global sensitivity (c-GSA) is presented, which is able to differentiate between the uncertainties even when GSA fails to do so. To demonstrate the value of c-GSA many small examples are presented. The third and the last key method in the Bayesian framework is the decision oriented design of experiment. Traditional 'Design of Experiment' (DOE) approaches focus on minimization of parameter error variance. In this work, a new "decision-oriented" DOE approach is proposed that takes into account how the generated data, and subsequently, the model developed based on them will be used in decision making. By doing so, the parameter variances get distributed in a manner such that its adverse impact on the targeted decision making is minimal. Results show that the new decision-oriented DOE approach significantly outperforms the standard D-optimal design approach. The new design method should be a valuable tool when experiments are conducted for the purpose of making R&D decisions. Finally, to demonstrate the importance of the overall Bayesian framework a bio-refinery case study is considered. The case study consists of the alternative to introduce a hemi-cellulose pre-extraction stage prior to pulping in a thermo-mechanical pulp mill. Application of the Bayesian framework to address this alternative, results in significant improvement in the prediction of the true potential value of the alternative.

In Bayesian decision analysis, uncertainty and risk are accounted for with probabilities for the possible states, or states of nature, that affect the outcome of a decision. Application of Bayes’ theorem requires non-informative prior probabilities, which represent the probabilities of states of nature for a decision maker under complete ignorance. These prior probabilities are then subsequently updated with any and all available information in assessing probabilities for making decisions. The conventional approach for the non-informative probability distribution is based on Bernoulli’s principle of insufficient reason. This principle assigns a uniform distribution to uncertain states when a decision maker has no information about the states of nature. The principle of insufficient reason has three difficulties: it may inadvertently provide a biased starting point for decision making, it does not provide a consistent set of probabilities, and it violates reasonable axioms of decision theory. The first objective of this study is to propose and describe a new method to establish non-informative prior probabilities for decision making under uncertainty. The proposed decision-based method is focuses on decision outcomes that include preference in decision alternatives and decision consequences. The second objective is to evaluate the logic and rationality basis of the proposed decision-based method. The decision-based method overcomes the three weaknesses associated with the principle of insufficient reason, and provides an unbiased starting point for decision making. It also produces consistent non-informative probabilities. Finally, the decision-based method satisfies axioms of decision theory that characterize the case of no information (or complete ignorance). The third and final objective is to demonstrate the application of the decision-based method to practical decision making problems in engineering. Four major practical implications are illustrated and discussed with these examples. First, the method is practical because it is feasible in decisions with a large number of decision alternatives and states of nature and it is applicable to both continuous and discrete random variables of finite and infinite ranges. Second, the method provides an objective way to establish non-informative prior probabilities that capture a highly nonlinear relationship between states of nature. Third, we can include any available information through Bayes’ theorem by updating the non-informative probabilities without the need to assume more than is actually contained in the information. Lastly, two different decision making problems with the same states of nature may have different non-informative probabilities. / text

Researchers have increasingly directed attention to the importance of emotions in decision making. Recent theories have focused on the interpersonal effects of emotions--the influence of the decision maker's expressed emotions on observers' decisions and judgments. In the current research, we examine people's expectations of how incidental, discrete emotions affect behavior. We also study how these expectations affect decisions in interactive settings, and contrast them with how emotions actually impact other people's behavior.These ideas were tested in four studies. In Study 1a, participants (N = 58) answered a questionnaire asking their perceptions of how different emotions affect behavior. In Study 1b, participants (N = 203) read a number of hypothetical scenarios in which different interactions between them and another person took place. Studies 2 (N = 98) and 3 (N = 132) were two economic games -- a Stag-Hunt game and a Trust Game -- involving decisions with non-trivial financial consequences.Across these four studies, I found that people do have strong beliefs about how incidental emotions affect behaviors. Because of these beliefs, when told about their counterparts' emotional state, people in interactive settings modify their behavior. The impact of people's beliefs on behavior, however, was more consistent for negative emotions such as anger and fear, than for positive emotions such as happiness and gratitude. These findings also indicate that people are sensitive to the different effects of different emotions: different negative emotions such as guilt and anger have different effects on their expectations. Finally, I found that people's expectations about how their counterparts' emotions affect behavior can be inaccurate in specific settings.

During their clinical practicum, nursing students are involved in making decisions about the care for their patient or group of patients. The purpose of this study was to ascertain nursing students' perceptions of the variety and magnitude of factors that influence them as they are making decisions about patient care. For the study a nonexperimental approach utlizing a cross-sectional descriptive design was used. Thirty-three second year and thirty-one third year nursing students from a diploma nursing school responded to a questionnaire designed to reflect perceived domains of influence in thier clinical decision making. A subset of 18 subjects were interviewed. Some of the major findings include: 1) More second year than third year students perceived stress as a factor affecting their clinical decision making. Third year students most often mentioned the instructor-student relationship as a source of stress. Second year students most often referred to their workload and fatigue as contributing to their stress. 2) More third year than second year students preceived decision making theory and the nursing process to be an influencing factor in decision making. 3) Previous life and health-related work experience was indicated to be an influencing factor in clinical decision making more often by second year students than by third year students. 4) When asked to choose and rank five from a list of sixteen influencing factors in clinical decision making, the combined group chose the following in order; knowledge of patients and their condition, level of self confidence, knowledge of nursing proces, relationship with instructor, previous nursing experience, and previous life experience. 5) In the interviews the two most frequently mentioned guiding forces in decision making were: (a)what they (the student) or someone close to them would want and (b)patient preference. The study encourages nursing instructors to be cognizant of the variety of forces impacting student decision making in the clinical setting. It also suggests that students who are encouraged to incorporate their personal reality in an atmosphere that provides some latitude in decision making will be more likely to assume decision-making responsibility. / viii, 96 leaves ; 28 cm.