Carbon dioxide capture and storage (CCS) is considered one of the key technologies for reducing atmospheric emissions of CO₂ from human activities (IPCC, 2005). The scale of potential deployment of CCS is enormous spanning manufacturing, power generation and hydrocarbon extraction worldwide. Uncertainty, cost-benefit challenges, market barriers and failures, and promotion and regulation of infrastructure are the main obstacles for deploying CCS technology in a broad scale. In a CCS project, it is the operator’s responsibility to guarantee the CO₂ containment while complying with environmental regulations and CO₂ contractual requirements with the source emitter. Acquiring new information (e.g. seismic, logs, production data, etc.) about a particular field can reduce the uncertainty about the reservoir properties and can (but not necessarily) influence the decisions affecting the deployment of a CCS project. The main objective of this study is to provide a decision-analysis framework to quantify the Value of Information (VOI) in a CCS project that faces uncertainties about permeability values in the reservoir. This uncertainty translates into risks of CO₂ migration out of the containment zone (or lease zone), non-compliance with contractual requirements on CO₂ storage capacity, and leakage of CO₂ to sources of Underground Source of Drinking Water (USDW). The field under analysis has been idealized based on a real project located in Texas. Subsurface modeling of the upper Frio Formation (injection zone) was conducted using well logs, field-specific GIS data, and other relevant published literature. The idealized model was run for different scenarios with different permeability distributions. The VOI was quantified by defining prior scenarios based on the current knowledge of a reservoir, contractual requirements, and regulatory constraints. The project operator has the option to obtain more reliable estimates of permeability, which will help to reduce the uncertainty of the CO₂ behavior and storage capacity of the formation. The accuracy of the information gathering activities is then applied to the prior probabilities (Bayesian inference) to infer the value of such data. / text

Value of information is one of the key features of decision analysis. This work deals with providing a consistent and functional methodology to determine VOI on proposed well tests in the presence of uncertainties. This method strives to show that VOI analysis with the help of discretized versions of continuous probability distributions with conventional decision trees can be very accurate if the optimal method of discrete approximation is chosen rather than opting for methods such as Monte Carlo simulation to determine the VOI. This need not necessarily mean loss of accuracy at the cost of simplifying probability calculations. Both the prior and posterior probability distributions are assumed to be continuous and are discretized to find the VOI. This results in two steps of discretizations in the decision tree. Another interesting feature is that there lies a level of decision making between the two discrete approximations in the decision tree. This sets it apart from conventional discretized models since the accuracy in this case does not follow the rules and conventions that normal discrete models follow because of the decision between the two discrete approximations. The initial part of the work deals with varying the number of points chosen in the discrete model to test their accuracy against different correlation coefficients between the information and the actual values. The latter part deals more with comparing different methods of existing discretization methods and establishing conditions under which each is optimal. The problem is comprehensively dealt with in the cases of both a risk neutral and a risk averse decision maker. / text

The grain and oil seed industry plays a major role in the South African economy; therefore, having access to market information is vital for this market to remain efficient and competitive. A shortage in market information causes many inefficiencies and uncertainties. Having market information allows the playing field to be level for all role players and reduces opportunities for manipulating prices. South Africa, just like most developing countries, needs to strengthen information flows, as well as institutions governing the grain and oil seed industry. In view of the major grain producing countries in the world and the amount of money and effort spent on releasing planting progress reports, the South Africa grain and oilseed sector should to take heed. This paper considers the importance of market information and how the South African grain and oil seed industry can benefit from that, grain planting progress reports are considered to be of importance as they fill a significant gap in the production season. Taking an institutional perspective into the economics of information, the study found that actors having little financial and social resources or political influence faced high costs in accessing information and that this prevents both market development and access to existing ones. The point of discussion is on weak information flows, as well as transaction costs that come with them, and the impact they have on prices and profitability. We therefore use New Institutional Economics to emphasise the importance of information in the market and the impact thereof in the absence of perfect information. The main underlying issue for imperfect information is that the lack of perfect and freely available information leads to risk and uncertainty in transactions. When trying to analyse the importance of information in the grain and oilseed industry, it was established that accuracy, value and market effect of information for public consumption were important. In particular, information communication technology was examined as a means of information dissemination in agriculture, especially in developing countries like South Africa. The study found that the major grain and oilseed producing countries that generate planting progress reports are the USA, Brazil, Argentina and Australia. The study looked at the methods used by these countries to compile such reports. Although they have varying methodologies, the key point is timely and frequent information which is readily available for public consumption. After analysing developments and methodologies globally, the focus shifted to South Africa where current information sources in the South African grain and oilseed industry, and the kind of information provided, were analysed. A pilot study was conducted in the summer grain production area of NWK Ltd to gain some insight and experience. The source of communication comprised mobile phones and farmers were able to respond on their progress, as well as receive feedback using the same communication media. Lastly in order to re-emphasis the benefits of a planting progress report, we review the impact of price volatility and how information in the market can help stabilise it. / Dissertation (MSc (Agric))--University of Pretoria, 2017. / Agricultural Economics, Extension and Rural Development / MSc (Agric) / Unrestricted

The intent of this dissertation is to generate a set of non-dominated finite-memory policies from which one of two agents (the leader) can select a most preferred policy to control a dynamic system that is also affected by the control decisions of the other agent (the follower). The problem is described by an infinite horizon total discounted reward, partially observed Markov game (POMG). Each agent’s policy assumes that the agent knows its current and recent state values, its recent actions, and the current and recent possibly inaccurate observations of the other agent’s state. For each candidate finite-memory leader policy, we assume the follower, fully aware of the leader policy, determines a policy that optimizes the follower’s criterion. The leader-follower assumption allows the POMG to be transformed into a specially structured, partially observed Markov decision process that we use to determine the follower’s best response policy for a given leader policy. We then present a value determination procedure to evaluate the performance of the leader for a given leader policy, based on which non-dominated set of leader polices can be selected by existing heuristic approaches. We then analyze how the value of the leader’s criterion changes due to changes in the leader’s quality of observation of the follower. We give conditions that insure improved observation quality will improve the leader’s value function, assuming that changes in the observation quality do not cause the follower to change its policy. We show that discontinuities in the value of the leader’ criterion, as a function of observation quality, can occur when the change of observation quality is significant enough for the follower to change its policy. We present conditions that determine when a discontinuity may occur and conditions that guarantee a discontinuity will not degrade the leader’s performance. This framework has been used to develop a dynamic risk analysis approach for U.S. food supply chains and to compare and create supply chain designs and sequential control strategies for risk mitigation.

Industry 4.0 is one of the fastest growing topics amongst both practitioners and academics. To this day, no definition of Industry 4.0 has reached consensus. However, some definitions can be considered more correct than others and the most accurate one is summarized as “Industry 4.0 is a concept for creating value throughout the whole value-chain”. This has been made possible through digital solutions, advanced technologies, which often are associated with Industry 4.0. This thesis started off finding the key aspects of Industry 4.0 and through a literature review it was concluded to be Cyber-Physical Systems (CPS) which will bring new innovative Business Models. The fundamental aspect of Industry 4.0 is data, data which has become available through the usage of CPS, data which will transform how business are conducted. This thesis aims to develop a better understanding for how CPS affects the Business Model. The thesis started with a literature review, investigating the value of information in a digitalized era. It was established that the value is found in the capability to monitor, remote control, optimize, and automate products and machines. Furthermore, it was also established through the literature review that manufacturing industries are becoming more services-focused and that value-creation is done through networking. Moreover, the Business Model Canvas was embraced as theoretical framework for what a business model should consist of. Data was gathered through semi-structured interviews with experts on the subject of Industry 4.0 and digitalization. The data was then compared to the theoretical framework. The results showed that CPS will not affect business models in any direct way as it is very well founded that the business model always should be based on the customer segment. However, CPS did have an indirect impact on business models i.e. through expected changes in customer relationships and distribution channels, but foremost, through changes regarding specialization and partnerships.

O cenário atual da gestão da informação é de extrema complexidade. A multiplicidade de ambientes computacionais gera extensos volumes de dados, mas nem sempre garante informações de qualidade. Elas embasam a maioria dos processos de tomadores de decisões. Nesse sentido, o presente estudo busca compreender a percepção da qualidade das informações entre profissionais e usuários de sistemas de informação. Além disso, desenvolve uma proposta de dimensões da qualidade baseadas no contexto de uso que, apesar de serem mais difíceis de mensurar, sustentam outras formas de qualidade da informação, adotadas ou não pelas organizações. O trabalho está dividido em duas partes. Primeiramente, levanta informações sobre a percepção da qualidade da informação entre os profissionais da informação, divididos em três perfis - produtores, consumidores e gestores da informação. Em seguida, avalia a classificação das dimensões propostas, considerando a importância de cada dimensão e a sua correspondente valorização para as organizações, na visão dos profissionais da informação. Os resultados do estudo podem orientar as organizações e, principalmente, os profissionais da área de Tecnologia da Informação, em relação à importância de adotarem práticas de melhoria da qualidade da informação. As dimensões propostas nesta classificação são baseadas no contexto de uso e, portanto, são as que estão mais próximas da realidade dos indivíduos que lidam com as informações, no dia a dia das organizações. / The present scenario of information management is extremely complex. The multitude of computing environments generates large volumes of data, but does not always guarantee quality information. They underlie most processes of decision makers. On this way, this work aims to understand the perception of the information quality for the professionals and users of information systems. Also, the work develops a classification proposal of quality dimensions based on the context of use. These, though harder to measure, maintain all other forms of information quality, used or not by organizations. The work has two specific objectives. First, gathering information on the perceived quality of information among information professionals, shared in three profiles - producers, consumers and managers of information. Secondly, assessing the classification of the dimensions proposed, considering the importance of each dimension and its corresponding value for the organizations, in accordance to the view of information professionals. The results of this work can guide organizations and especially the professionals, about the importance of adopting practices to improve the quality of information. The proposed classification is based on the context, therefore, although they are difficult to be measured, they are also those which are closest to the reality of individuals who deal with the information, every days in the organizations.

O cenário atual da gestão da informação é de extrema complexidade. A multiplicidade de ambientes computacionais gera extensos volumes de dados, mas nem sempre garante informações de qualidade. Elas embasam a maioria dos processos de tomadores de decisões. Nesse sentido, o presente estudo busca compreender a percepção da qualidade das informações entre profissionais e usuários de sistemas de informação. Além disso, desenvolve uma proposta de dimensões da qualidade baseadas no contexto de uso que, apesar de serem mais difíceis de mensurar, sustentam outras formas de qualidade da informação, adotadas ou não pelas organizações. O trabalho está dividido em duas partes. Primeiramente, levanta informações sobre a percepção da qualidade da informação entre os profissionais da informação, divididos em três perfis - produtores, consumidores e gestores da informação. Em seguida, avalia a classificação das dimensões propostas, considerando a importância de cada dimensão e a sua correspondente valorização para as organizações, na visão dos profissionais da informação. Os resultados do estudo podem orientar as organizações e, principalmente, os profissionais da área de Tecnologia da Informação, em relação à importância de adotarem práticas de melhoria da qualidade da informação. As dimensões propostas nesta classificação são baseadas no contexto de uso e, portanto, são as que estão mais próximas da realidade dos indivíduos que lidam com as informações, no dia a dia das organizações. / The present scenario of information management is extremely complex. The multitude of computing environments generates large volumes of data, but does not always guarantee quality information. They underlie most processes of decision makers. On this way, this work aims to understand the perception of the information quality for the professionals and users of information systems. Also, the work develops a classification proposal of quality dimensions based on the context of use. These, though harder to measure, maintain all other forms of information quality, used or not by organizations. The work has two specific objectives. First, gathering information on the perceived quality of information among information professionals, shared in three profiles - producers, consumers and managers of information. Secondly, assessing the classification of the dimensions proposed, considering the importance of each dimension and its corresponding value for the organizations, in accordance to the view of information professionals. The results of this work can guide organizations and especially the professionals, about the importance of adopting practices to improve the quality of information. The proposed classification is based on the context, therefore, although they are difficult to be measured, they are also those which are closest to the reality of individuals who deal with the information, every days in the organizations.

In this study, value of demand information and the importance of option contracts are investigated for a supply chain consisting of a buyer and two suppliers in a single period setting. One supplier is cheap but prone to disruptions whereas the other one is perfectly reliable but expensive. At the beginning of the period, buyer orders from the unreliable supplier and reserves from the reliable supplier through a contract that gives buyer an option to use reserved units after getting disruption information of first supplier. We introduce three models which differ in terms of the level of information available when the ordering decisions are made. In the full information model, the options are exercised after getting disruption and demand information / in the partial information model, the options are exercised after getting disruption information before demand information. In the no information model, there is no options contract and units are ordered from the reliable supplier when buyer has no information about demand and disruption. Through the analysis of these models, we explore the value of advance demand and disruption information in the presence of an options contract.

This thesis studies the impact of sequential auction design on participant behavior from both a theoretical and an empirical viewpoint. In the first of the two analyses, three sequential auction designs are characterized and compared based on expected profitability to the participants. The optimal bid strategy is derived as well. One of the designs, the alternating design, is a new auction design and is a blend of the other two. It assumes that the ability to bid in or initiate an auction is given to each side of the market in an alternating fashion to simulate seasonal markets. The conditions for an equilibrium auction design are derived and characteristics of the equilibrium are outlined. The primary result is that the alternating auction is a viable compromise auction design when buyers and suppliers disagree on whether to hold a sequence of forward or reverse auctions. We also found the value of information on future private value for a strategic supplier in a two-period case of the alternating and reverse auction designs. The empirical work studies the cause of low aggregation of timber supply in reverse auctions of an online timber exchange. Unlike previous research results regarding timber auctions, which focus on offline public auctions held by the U.S. Forest Service, we study online private auctions between logging companies and mills. A limited survey of the online auction data revealed that the auctions were successful less than 50% of the time. Regression analysis is used to determine which internal and external factors to the auction affect the aggregation of timber in an effort to determine the reason that so few auctions succeeded. The analysis revealed that the number of bidders, the description of the good and the volume demanded had a significant influence on the amount of timber supplied through the online auction exchange. A plausible explanation for the low aggregation is that the exchange was better suited to check the availability for custom cuts of timber and to transact standard timber.

An important element of successful engineering design is the effective management of resources to support design decisions. Design decisions can be thought of as having two phasesa formulation phase and a solution phase. As part of the formulation phase, engineers must decide how much information to collect and which models to use to support the design decision. Since more information and more accurate models come at a greater cost, a cost-benefit trade-off must be made. Previous work has considered such trade-offs in decision problems when all aspects of the decision problem can be represented using precise probabilities, an assumption that is not justified when information is sparse. In this thesis, we use imprecise probabilities to manage the information cost-benefit trade-off for two decision problems in which the quality of the information is imprecise: 1) The decision of when to stop collecting statistical data about a quantity that is characterized by a probability distribution with unknown parameters; and 2) The selection of the most preferred model to help guide a particular design decision when the model accuracy is characterized as an interval. For each case, a separate novel approach is developed in which the principles of information economics are incorporated into the information management decision. The problem of statistical data collection is explored with a pressure vessel design. This design problem requires the characterization of the probability distribution that describes a novel material's strength. The model selection approach is explored with the design of an I-beam structure. The designer must decide how accurate of a model to use to predict the maximum deflection in the span of the structure. For both problems, it is concluded that the information economic approach developed in this thesis can assist engineers in their information management decisions.