The importance of health and quality health care in people’s daily lives is widely recognised. Physicians play a key role in delivering quality health care and improved patient outcomes. However, the evidence regarding physicians’ decision making and their perception of quality of health care delivery and its influencers is inconclusive. The overall aim of this thesis is to increase the understanding of quality in health care delivery and the factors that influence it from a physician’s perspective. This aim is fulfilled by conducting three interlinked research projects. The first research project comprises a systematic review of the literature that identifies the factors, contexts and theoretical underpinnings influencing physician decision making. The synthesis of 160 studies reveals two main categories of influencing factors. The first is ‘Contexts’, which refers to the set of circumstances or facts surrounding a particular event or situation. The second category is ‘Interventions’, which are the techniques, processes or actions introduced to create changes in how physicians make decisions while performing their clinical duties. Although extant literature provides ample evidence on factors influencing physician decision making the link to quality in health care is under researched. In the second research project, the author explores how physicians construct quality of health care delivery by means of investigating 162 clinical cases with 27 repertory gird interviews that yield eleven key constructs representing a classification of physicians’ conception of quality. The third research project examines physicians’ perceptions of enablers and barriers to quality in health care delivery, employing semi-structured interviews. Findings indicate that physician’s effort in delivering quality health care is largely influenced by factors affecting behavioural control (freedom to act). This research makes five contributions to knowledge. First, a novel classification of factors influencing physician decision making when prescribing is developed, providing new understanding of the link between these factors and quality of health care. Second, the systematic review shows an innovative application of factor analysis to structure the findings of a complex phenomenon. Third, the study presents a new conceptualisation of physicians’ construction of quality in health care. Fourth, the research provides a categorization of physicians’ perceived enablers and barriers to quality health care and the mechanisms by which they operate. Finally, this research develops a theoretically-grounded and empirically-informed conceptual model that incorporates three hitherto separate domains: agency, planned behaviour, and decision theories. This model provides a new integrated lens to better understand the complexities influencing quality in health care delivery. This study also makes two significant contributions to practice. First, the findings have helped initiate a transformation in the pharmaceutical industry’s business model, evolving from business-to-person to business-to-business. Second, the findings serve as a catalyst to drive organizational changes at Norway’s largest emergency hospital. As a result, a national debate was initiated, involving the Prime Minister and Minister of Health, on how hospital emergency care can best be provided at a national level.

Title: Managing an emerging region – A study of how MNCs manage uncertainty in a Southern African context Authors: Markus Axelsson & Andreas Olofsson Supervisor: Cecilia Pahlberg Research question: How are Swedish business-to-business MNCs reducing perceived uncertainty when operating in the Southern African Development Community? Purpose: Provide a deeper understanding of how Swedish MNCs from diverse industrial backgrounds are managing uncertainty when operating in the Southern African Development Community (SADC). This study further aims to add to an acknowledged theoretical gap in international business research by providing a contextual contribution towards the Southern African region to the field of internationalization management. Method: A qualitative research method including semi-structured interviews was used to gain in- depth understanding of how Swedish B2B MNCs manages uncertainty within SADC markets. For the analysis, a theoretical framework based on uncertainty management, knowledge and network theory was developed into a conceptual model, carried out when gathering empirical data. Conclusions: The findings suggest that gaining experiential knowledge was vital to reduce perceived uncertainty among Swedish B2B MNCs operating in SADC markets. Experiential knowledge was obtained through operations within the markets, which over time resulted in enhanced market commitments and thereafter increased experiential knowledge. Knowledge was further exclusively shared within networks, where gaining network insidership was essential. To gain network insidership in SADC markets, findings suggest that becoming localized in the market to gain legitimacy is beneficial and achieved over a longer period of time. Finally, findings indicate that South Africa could be used as a gateway into Southern Africa, where firms’ can gain valuable experiences, relationships and an understanding of business practices, which can reduce the perceived uncertainty towards other SADC markets.

published_or_final_version / Economics and Finance / Master / Master of Economics

The purpose of this dissertation is to explore how the economic return of a software investment can be assessed and managed. This topic has been studied in research and has been a concern for firms making software investments. In order to study this we need a model of the underlying factors affecting the economic return. Assessing and managing the return of a software investment is been argued to be difficult due to specific economic characteristics of a software investment, i.e. high degree of intangible consequences and uncertainty about the total investment cost. Given these characteristics it is has been concluded that it is difficult to derive a return function. In this dissertation we question this conclusion and propose a comprehensive model to assess and manage the intangibles and the underlying uncertainty. The model is deduced from general assumptions of the economic behavior of the firm. To develop the model we analyze the relevance of intangibles in relation to the economic purpose of making a software investment. Based on this a new way of deriving a cash flow function for a software investments is defined. Further it is analyzed how the underlying uncertainty of a software investment can be managed. The analysis uses a quantitative approach and methods from financial economics. It includes how the application of a real option and portfolio approach can reduce the uncertainty in a software investment and the role of efficient software platforms. The relation between software platforms and the opportunity to create different types of real options for future development is inferred from empirical studies. The studies in this dissertation show how a managerial view on a software investment corresponds with the overall economic goal of the firm. They also show how a strategic value of a software investment can be created, assessed and managed.

In the screening and concept selection stages of gas storage projects, many estimates are required to value competing projects and development concepts. These estimates are important because they influence which projects are selected and which concept proceeds into detailed engineering. In most cases, there is uncertainty in all of the estimates. As a result, operators are faced with the complex problem of determining the optimal design. A systematic uncertainty analysis can help operators solve this problem and make better decisions. Ideally, the uncertainty analysis is comprehensive and includes all uncertain variables, and simultaneously accounts for reservoir behavior, facility options, and economic objectives. This thesis proposes and demonstrates a workflow and an integrated optimization model for uncertainty analysis in gas storage. The optimization model is fast-solving and eliminates most constraints on the scope of the uncertainty analysis. Using this or similar workflows and models should facilitate analysis and communication of results within the project team and with other stakeholders. / text

Uncertainty surrounds the future evolution of key factors affecting the attractiveness of various nuclear fuel cycles, rendering the concept of a unique optimal fuel cycle transition strategy invalid. This work applies decision-making under uncertainty to fuel cycle transition analysis, demonstrating a new, systematic methodology for choosing flexible, adaptable hedging strategies that yield middle-of-the-road results until uncertainties are resolved. A case study involving transition from the current once-through light water reactor (LWR) fuel cycle to one relying on continuous recycle in fast reactors (FRs) is cast as a no-data decision problem. The transition is subject to uncertainty in the cost of spent nuclear fuel (SNF) and high-level waste (HLW) disposal in a geologic repository, slated to open some years into the future. Following the repository open date, the cost of SNF and HLW disposal is made known, and may take on one of five possible values. Strategies for the transition are enumerated and simulated using VEGAS, a systems model of the nuclear fuel cycle that solves for its material balance and applies input cost data to calculate the associated annual levelized cost of electricity (LCOE). Perfect information strategies are found using the lowest average, maximum, and integrated LCOE objective functions. The loss in savings for following a strategy other than the perfect information strategy is the “regret” which is calculated by evaluating the performance of each strategy for every end-state. Hedging strategies are then selected by either minimizing the maximum or the expected regret. Generally, the optimal hedging strategy identified using the decision methodology suggests a partial transition to a closed fuel cycle prior to the repository open date. Once the repository opens, the transition may be abandoned or accelerated depending on which disposal cost outcome is realized. The lowest average and integrated LCOE objective functions perform similarly; however, the lowest maximum LCOE objective function appears overly sensitive to aberrations in the annual LCOE that arise due to idle reprocessing capacity. The minimax regret choice criterion is shown to be more conservative than the lowest expected regret choice criterion, as it acts to hedge against the worst-case outcome. By following a hedging strategy, agents may alter their fuel cycle strategy more readily once uncertainties are resolved. This results since hedging strategies provide flexibility in the nuclear fuel cycle, preserving what options exist. To this end, the work presented here may provide guidance for agent-based, behavioral modeling in fuel cycle simulators, as well as decision-making in real world applications. / text

<p>The internationalization process is usually viewed from an outward- perspective ininternational business literature. In this thesis the focus is put on an outward-inwardinterrelationship perspective. An extensive literature review from literature in internationalbusiness literature, entrepreneurial literature as well as international marketing literature wasconducted in order to extract key variables that affect the process of internationalization of thefirm. The key variables that were examined were: Business Contacts, InternationalExperience, Perceived International Opportunity and Perceived International Uncertainty.A qualitative interview with semi-structured questions was conducted in order to construct amodel that should be used as the basis for a quantitative study of an inward-driveninternationalization process, in order to generalize. The results were in line with thepropositions based on the relationships between the variables. In other words, the constructedmodel and the developed questionnaire were of use when examining the relationship betweenthe variables and seem to be of value when applied to an inward oriented context. Thevariable International Experience received the highest score and seemed to reflect animportant contribution for the internationalization process. Nevertheless, further quantitativeresearch is asked for, in order to support the results and be able to generalize.</p>

<p>The purpose of this study is to investigate how individual retirement savings are made tangible for potential customers. As case companies we have studied the marketing strategies of Handelsbanken and Swedbank.</p><p>We use Miller and Foust’s classification of services by intangibility based on attributes and benefits and Tarn’s four strategy marketing-based model in order to find out how the retirement savings are made tangible.</p><p>We find that the attributes and benefits that are used to define retirement savings depend on how the service is affiliated to life-insurance or banking services. Intangibility is coped by simplifying the products by lifting forward salient features. Complexity is overcome by explanation. Putting emphasis on flexibility is a mean to cope with the uncertainty of future income.</p>

Decisions for asset allocation and protection are predicated upon accurate knowledge of the current operating environment as well as correctly characterizing the evolution of the environment over time. The desired kinematic and kinetic states of objects in question cannot be measured directly in most cases and instead are inferred or estimated from available measurements using a filtering process. Often, nonlinear transformations between the measurement domain and desired state domain distort the state domain probability density function yielding a form which does not necessarily resemble the form assumed in the filtering algorithm. The distortion effect must be understood in greater detail and appropriately accounted for so that even if sensors, state estimation algorithms, and state propagation algorithms operate in different domains, they can all be effectively utilized without any information loss due to domain transformations. This research presents an analytical investigation into understanding how non-linear transformations of stochastic, but characterizable, processes affect state and uncertainty estimation with direct application to space object surveillance and space- craft attitude determination. Analysis is performed with attention to construction of the state domain probability density function since state uncertainty and correlation are derived from the statistical moments of the probability density function. Analytical characterization of the effect nonlinear transformations impart on the structure of state probability density functions has direct application to conventional non- linear filtering and propagation algorithms in three areas: (1) understanding how smoothing algorithms used to estimate indirectly observed states impact state uncertainty, (2) justification or refutation of assumed state uncertainty distribution for more realistic uncertainty quantification, and (3) analytic automation of initial state estimate and covariance in lieu of user tuning. A nonlinear filtering algorithm based upon Bayes’ Theorem is presented to ac- count for the impact nonlinear domain transformations impart on probability density functions during the measurement update and propagation phases. The algorithm is able to accommodate different combinations of sensors for state estimation which can also be used to hypothesize system parameters or unknown states from available measurements because information is able to appropriately accounted for.

Background: A university is characterized as organized anarchy. According to Cohen, et al. (1972) decision-making occurs in form of A Garbage Can Model (GCM) in such organizations. This model is influenced by some factors such as organizational structure. The influences of some types of organizational structure have been studied based on a computer simulation by Cohen and his colleagues in 1972. However, the study was based on numerical statistics and excluded the influence of genuine characteristics of an organizational structure. Aim: This thesis aims to understand the influence of the dynamic and real characteristics of an organizational structure on a university’s decision-making process. Therefore, this research is conducted to explore how matrix structure influences on decision-making process in Linköping University by reducing uncertainty characteristics of decision-making process. Definitions: A Garbage Can Model: provides a theory framework in order to understand how decisions are made in organizations under condition of organized anarchy. This Model has four heterogeneous streams include decision, solution, decision maker, and choice opportunity. All these streams are moving around within the organization and need to match up in the choice opportunities to make decisions. Matrix Structure: is a structure with focus on multiple dimensions through multiple lines of authority and lateral communication. Results: The Matrix structure reduces the uncertainty of decision-making in Linköping University by managing the information process through the lateral communication. More specifically, the lateral communication occurs based on different approaches such as informal meetings, network of people, management group, and external information. However, the authority aspect in Linköping University has certain tendency towards the single unity of command (centralization), which is in contrast with matrix structure characteristics.