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In this thesis the target is to find the optimal development solution of an offshore natural gas field. Natural gas is increasing in importance as an energy source. Whilst most of the large oil fields have been developed, there are still several major natural gas deposits that may be developed. In addition, there are also smaller offshore natural gas fields that may be put into production. Finding an optimal development solution for these resources will increase the availability of natural gas.The objective of the mathematical model presented in this thesis is to maximize the total net present value of an offshore natural gas field development. The model does this by finding the optimal combination of investment decisions of the necessary natural gas field infrastructure. Infrastructure included in the model includes the number of wells to be drilled, flowlines, production facilities, energy infrastructure on site and transport infrastructure to the customers. The model also decides whether gas sales agreements should be made with selected customers and the natural gas production in all time periods.This offshore natural gas field development problem is formulated as a mixed integer linear programming problem. Piecewise linearization is used to increase the accuracy of the reservoir model and to find the energy demand for a given natural gas flow rate and pressure difference. The linearization makes the model easier to solve than if it was formulated as a non-linear program.Branch and bound was chosen as the solution method for the implementation of the model. The model has been implemented in the Mosel programming language, using Xpress-MP as the solver.Results from testing of the model on three different test cases indicate promising potential for the utilisation of the model. Optimal solutions were found in less than six minutes for all of the test cases, and close to optimal solutions were found quickly in the global search.

There is an ever-increasing interest towards the field of purchasing and much attention has been placed towards the importance of purchasing in relation to firms’ survival in a competitive environment. In general, firms have an array of interrelated activities from operational production, to marketing and R&D. However, all firms also typically conduct purchase activities, hence the chain of activities is only as strong as its weakest link. Further, in many industries firms spend more than half of their revenue on purchasing materials and services. This can be explained through the trend of firms to exclude non-critical activities out to other actors under the banner of outsourcing. This trend on the other hand implies that higher responsibilities have been placed on the suppliers and their specific product contributions to the buying firm. Therefore, the implication is that firms have to develop appropriate supplier strategies based on what type of commodity they are buying. In this thesis the theme is sourcing strategy and addresses this issue. A case study of a construction firm is carried out in this thesis to analyze their purchasing practice, and the objective is to find improvement areas for the case firm in relation to the various uses of sourcing strategies. In order to do that a literature review is conducted to explore and relate the various sourcing strategy models in an effort to compare these findings with observed practice of the case firm.The result of the literature review shows that there are in general four main aspects to consider in relation to sourcing strategy: (1) what strategy for a given commodity, (2) how many suppliers, (3) what kind of relationships to pursue, and (4) how do we structure the supply base. With these aspects at hand, the author analyzed the case firm and in particular within an ongoing construction project to find improvement areas.The findings of the empirical study is that the observed practice of the case firm to some extend resembles the theoretical frameworks in the sourcing literature. The firm uses distinctive strategies based on what commodities they are buying, however, due to the construction industry’s specific characteristics, the firm has adapted or reconfigured it to suit their business. Further, by mapping how the supply base of the given project is structured, it resembles what the literature call parallel sourcing.The thesis concludes that even though the case firm’s practice resembles parallel sourcing, the practice does not fully reap the benefits depicted by the literature. In order to fully benefit, the case firm is recommended to consider the development of long-term relationships with a limited set of suppliers. By doing so, this would coincide more with the literature’s description of parallel sourcing, and hence harvest the same benefits that are argued by the literature.

This paper applies various ways of constructing statistical arbitrage trading rules for aluminum securities. The paper use daily observations of stocks, futures and two securities supposed to mirror the return of physical aluminum. We employ several sophisticated analysis of thestatistical properties of these securities and how they relate to each other. This paper appliesEngle-Granger and Johansen tests for cointegration to identify suitable securities for pairstrading. The paper is useful for speculators and hedge fund managers who want to increase theirrisk adjusted returns, as our analysis shows that trading sector neutral positions instead ofholding passive long positions in aluminum securities have significantly higher risk adjustedreturns. Our methodology is not unique for aluminum and can be transferred to other areas suchas oil or precious metals.

Over the last years, rapid technological development has made it possible for organizations to increase their use of virtual teams. Unlike traditional face-to-face teams, virtual teams enable people to collaborate across virtual dimensions like geographical dispersion, time and cultural diversity. By making use of virtual teams, organizations are able to increase the efficiency and performance, as they can be more flexible than traditional face-to-face teams. There has been an increased focus on research within this field of work in line with the development of virtual teams. However, there are few studies that have investigated the affect virtual teams as a work process has on collaborative relationships across organizational boundaries. This Master thesis is analyzing how inter-organizational relationships in the oil and gas industry can be affected by implementing Integrated Operations (IO) to their work processes. IO is a strategic tool using information and communication technology in order to change work practices and enabling people and organizations within this industry to work together through virtual communication channels. Organizations use virtual teams by installing collaboration rooms equipped with video walls and sound. In these rooms, people can communicate in real-time and across large geographical distances. This can potentially increase the effectiveness and simplifies collaboration both offshore and onshore. This study describes new challenges and opportunities in inter-organizational relationships between operator companies and suppliers due to the implementation of IO, and how working in virtual teams influences the relationships. In order to explore these issues, a case study of a business relationship between two companies in the oil and gas industry has been conducted, where collaboration takes place across geographical distance and across organizational boundaries. These companies are using virtual teams as a basis for their collaborative work. Their interaction through virtual communication channels has been observed over a significant period of time, and semi-structured interviews have been used to support the findings from the observations. This is done in order to analyze the potential and challenges of implementing IO in this industry.The main findings in this study show that there is a great potential for using virtual teams when interacting across organizational boundaries. Operator companies and suppliers have the opportunity of developing closer relations by working in virtual teams as such teams simplify the processes of communicating. However, there are some significant challenges. Virtual teams are most successful when the actors collaborating have a personal relationship. This if most often the case when actors within the same organization are working together. People that are collaborating through inter-organizational relationship may have less knowledge of each other. Relationships where the organizations have an unequal power structure due to their size and influence in the oil and gas industry can be especially challenging. As the actors are trying to protect their own organization’s interest, an unequal power structure can question the level of trust and potential for value creation within the team. This can potentially create boundaries and limitations when communicating through virtual communication channels as interaction through videoconference systems creates a less personal environment than traditional face-to-face communication. The main contribution of this study is that: taking use of virtual dimension in inter-organizational relationships increases the potential level of conflicts between organizations, complicates the communication process and consolidates the power structure in the relationship between the collaborating parties.

Through a dynamic panel data analysis of a sample of Nordic firms we investigate how executives’ stock and option incentives influence the choice of capital structure. In addition, we look at how equity ownership by a large external shareholder influences the incentives’ effect on capital structure. Our results show that options have a negative effect on debt level, while stock holdings’ influence is more diffuse. We also see that only options have both a statistical and economical significant impact on leverage, and therefore operate as a stronger incentive than stocks. No significant dependency is found between the size of the largest external shareholder and the incentives’ effect on capital structure. Still, we see a weak trend indicating that the effect of equity based incentives is stronger when firms’ largest shareholders are institutional.

This thesis aims to map out the current state of the Norwegian power industry and reveal opportunities that can serve as a fundament for the formation of new business models in the industry post AMR implementation.Demand side management (DSM) arouse to include end customers and give them incentives for having a power consumption pattern which also benefits the power system. Market structure; lack of ICT infrastructure and understanding of the solutions; costs and competitiveness, as well as the lack of incentives are currently some of the most critical barriers to DSM implementation. However, the forthcoming establishment of a smarter transmission grid is expected to easier facilitate DSM actions. A smart grid facilitates transmission of information in addition to power, and is hence more intelligent than today’s grid as it can integrate the behavior of all connected users. A smart grid is not one single installation, but consists of several components, of which automatic meter reading (AMR) is one. The drivers for implementing a smarter grid in Norway differ from the prevailing European drivers. In Norway, the progress towards a smarter grid is driven by the desire to reduce peak loads and create a secure power system which benefits the end customer. Implementation of AMR has been adopted in Norway, although the specific functionalities and responsibilities are not yet entirely determined. In addition to AMR implementation, a common Nordic end user market is also expected within the coming years. We expect the supplier centric model (SCM) to become the chosen market model. This involves a single contact point for the end customer, so that the supplier will handle most customer specific issues. AMR is expected to facilitate innovation opportunities that potentially can lead to a disruptive change of the industry. Dependent on current position, industry actors must determine whether to act as a first-mover or a fast second when taking positions in the future industry. End customer support is decisive for diffusion of the additional technological functionalities AMR can provide. Four key subjects for examining fundamental conditions for the formation of new business models in this market concern industry changes; a possible redistribution of responsibilities and roles; mapping of market forces and last but not least revealing unrealized value in the value chain. We find that a redistribution of roles in the electrical power market is probable, and that the actor most exposed to changes and new industry actors are the power suppliers. An assessment of market forces in the industry after AMR implementation shows that the end customer has the most power and is of great significance for the development of the industry. We reveal unrealized value in customer relations, customer flexibility and metering data. AMR has disruptive characteristics, and competitive companies spotting disruptive change in advance can choose between defending against the threat and utilizing this change. Due to uncertainty, companies are in danger of underestimating the potential impact of future disruptive changes. Existing power suppliers should enter into alliances to obtain future required qualities for success, such as flexibility, ICT knowledge and innovation skills. In order to achieve desired diffusion of new innovations, companies should be aware of the importance of mapping customers’ behavior and willingness to adopt new solutions. The revealed unrealized value can take different expressions in the future market. Metering data facilitate development of additional solutions on the AMR platform. The customer flexibility is extremely valuable but currently difficult to access. Transactions of flexibility from end customers can follow four different models, dependent on who is buying flexibility. Three different future scenarios for customer relations are predicted; fully separated activities, concentrated activity bundling and fragmented activity bundling, dependent on whether the customer relates to one or more power suppliers and service providers. We expect an industry revolution which will favor companies which are close to the customer and which are flexible and possess competencies within innovation and ICT. Accessing the three sources of unrealized value, which are all customer related, can give competitive advantage and serve as a fundament for the formation of new business models in the Norwegian power industry post AMR implementation.

Using an event study approach on a sample of 72 acquisitions by Norwegian listed firms we study the effect of CEO stock and options based incentives on abnormal return and risk change associated with M&A activity. Our focus is on the bidder firms’ pre-acquisition incentive structures and its effect on the abnormal return and risk change from the transaction. The regression analysis we perform supports the hypothesis that cultural differences lead to different effects of equity based incentives in Norwegian compared to US firms. We find that CEO stock options decrease bidder shareholder returns in M&A, while CEO stock ownership has a non-significant negative influence. Both incentive structures have an insignificant impact on the CEOs’ risk taking behavior. Accordingly, we cannot recommend that shareholders use stocks or options to reduce agency problems.The thesis provides a platform on which shareholders in Norwegian firms can build their decisions regarding the optimal incentive contract for their CEO. However, our limited sample and the lack of supportive research for other markets outside the US, does not allow for generalizing our findings to markets outside Norway.

This paper compares the Value at Risk (VaR) forecasting performance of different quantile regression models to conventional GARCH specifications on the Nord Pool system price. The sample covers hourly data from 2005-2011. In order to identify significant explanatory variables, we use a linear quantile regression to characterize the effects of fundamental factors on the system price formations. From our analysis we are able to show how the sensitivity of the variables change over the range of price quantiles and detect how these sensitivities vary over the hours of the day. Our findings suggest that the demand forecast and the price volatility is the most important determinants of the price in the tails of the distribution. We use these variables in the further analysis and test the out-of-sample VaR performance of linear quantile regression, exponentially weighted quantile regression (EWQR) and conditional autoregressive value at risk (CAViaR) models on the system price. We extend the CAViaR models to account for asymmetrical response to returns and are innovative in including explanatory variables in the CAViaR specification. Our results show that the I-GARCHX CAViaR model with demand forecast as explanatory variable outperform the other models, and that CAViaR models in general perform well. The linear quantile regression with price volatility as explanatory variable also provides good results. The computational complexity of CAViaR models favors a linear quantile regression, so market participants have to make a tradeoff between the level of accuracy in the forecasts and the complexity of the model. Our findings are useful for producers, consumers and traders, as well as clearinghouses, as they provide an accurate measure of the price risk.

The combination of risk management and cost allocation in order to allocate risk in a sensible manner is a field with not much existing theory. The ABC (Activity Based Costing) model seems as an appropriate cost allocation method, with a structure of using activities as a connecting link. ERM (Enterprise Risk Management) is selected as foundation for the risk management theory because it provides a general framework and a holistic approach. Furthermore, we choose to use four main risk categories. Some hypothetical ABRM (Activity Based Risk Management) alternatives based on these can be used to allocate risk. These alternatives include approaches where risk is allocated to products either from the bottom and up (bottom-up) or from the top and down (top-down). The top-down approach is most suitable when the total risk is known, while the bottom-up is most suitable when a risk category should be divided into sub-categories. A combination of the two approaches may also be of purpose. A qualitative research is conducted among Norwegian banks and power companies in order to map current risk practice. This empirical results show that banks are more sophisticated regarding both cost allocation and risk management, but neither of banks and power companies use ABC extensively, in fact the product calculations are independent of the ABC allocations. Banks have a customer focus instead of emphasizing products.If risk can be divided into overhead and direct as for costs, this fact along with the empirical findings gives a good foundation for discussing the hypothetical alternatives. Another alternative is added to better handle complex risk categories, like e.g. concentration risk. It also becomes apparent that the manufacturing industry, which we believe uses ABC for calculating product profitability, can apply all the discussed alternatives in this thesis, whereas banks and power companies can only use some of them. Regarding the question of whether or not the ABRM alternatives would be of purpose or not, this is not easy to answer before having applied it in the real world and judged its results (even after having conducted a research of banks and power companies). However, attention-directing information can be gained, and the present paper is only meant as an introductory discussion to the topic, and will hopefully provide some innovative input to the world of risk management.