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Under deregulated electric market, electricity price is no longer set by the monopoly utility company rather it responds to the market and operating conditions. Offering the right amount of electricity at the right time with the right bidding price has become the key for utility companies pursuing maximum profits under deregulated electricity market. Therefore, electricity market clearing price (MCP) forecasting became essential for decision making, scheduling and bidding strategy planning purposes. However, forecasting electricity MCP is a very difficult problem due to uncertainties associated with input variables.<p> Neural network based approach promises to be an effective forecasting tool in an environment with high degree of non-linearity and uncertainty. Although there are several techniques available for short-term MCP forecasting, very little has been done to do mid-term MCP forecasting. Two new artificial neural networks have been proposed and reported in this thesis that can be utilized to forecast mid-term daily peak and mid-term hourly electricity MCP. The proposed neural networks can simulate the electricity MCP with electricity hourly demand, electricity daily peak demand, natural gas price and precipitation as input variables. Two situations have been considered; electricity MCP forecasting under real deregulated electric market and electricity MCP forecasting under deregulated electric market with perfect competition. The PJM interconnect system has been utilized for numerical results. Techniques have been developed to overcome difficulties in training the neural network and improve the training results.

In previous research on pricing mortality-linked securities, the no-arbitrage approach is often used. However, this method, which takes market prices as given, is difficult to implement in today's embryonic market where there are few traded securities. In particular, with limited market price data, identifying a risk neutral measure requires strong assumptions. In this thesis, we approach the pricing problem from a different angle by considering economic methods. We propose pricing approaches in both competitive market and non-competitive market. In the competitive market, we treat the pricing work as a Walrasian tâtonnement process, in which prices are determined through a gradual calibration of supply and demand. Such a pricing framework provides with us a pair of supply and demand curves. From these curves we can tell if there will be any trade between the counterparties, and if there will, at what price the mortality-linked security will be traded. This method does not require the market prices of other mortality-linked securities as input. This can spare us from the problems associated with the lack of market price data. We extend the pricing framework to incorporate population basis risk, which arises when a pension plan relies on standardized instruments to hedge its longevity risk exposure. This extension allows us to obtain the price and trading quantity of mortality-linked securities in the presence of population basis risk. The resulting supply and demand curves help us understand how population basis risk would affect the behaviors of agents. We apply the method to a hypothetical longevity bond, using real mortality data from different populations. Our illustrations show that, interestingly, population basis risk can affect the price of a mortality-linked security in different directions, depending on the properties of the populations involved. We have also examined the impact of transitory mortality jumps on trading in a competitive market. Mortality dynamics are subject to jumps, which are due to events such as the Spanish flu in 1918. Such jumps can have a significant impact on prices of mortality-linked securities, and therefore should be taken into account in modeling. Although several single-population mortality models with jump effects have been developed, they are not adequate for trades in which population basis risk exists. We first develop a two-population mortality model with transitory jump effects, and then we use the proposed mortality model to examine how mortality jumps may affect the supply and demand of mortality-linked securities. Finally, we model the pricing process in a non-competitive market as a bargaining game. Nash's bargaining solution is applied to obtain a unique trading contract. With no requirement of a competitive market, this approach is more appropriate for the current mortality-linked security market. We compare this approach with the other proposed pricing method. It is found that both pricing methods lead to Pareto optimal outcomes.

Under deregulated electric market, electricity price is no longer set by the monopoly utility company rather it responds to the market and operating conditions. Offering the right amount of electricity at the right time with the right bidding price has become the key for utility companies pursuing maximum profits under deregulated electricity market. Therefore, electricity market clearing price (MCP) forecasting became essential for decision making, scheduling and bidding strategy planning purposes. However, forecasting electricity MCP is a very difficult problem due to uncertainties associated with input variables.<p> Neural network based approach promises to be an effective forecasting tool in an environment with high degree of non-linearity and uncertainty. Although there are several techniques available for short-term MCP forecasting, very little has been done to do mid-term MCP forecasting. Two new artificial neural networks have been proposed and reported in this thesis that can be utilized to forecast mid-term daily peak and mid-term hourly electricity MCP. The proposed neural networks can simulate the electricity MCP with electricity hourly demand, electricity daily peak demand, natural gas price and precipitation as input variables. Two situations have been considered; electricity MCP forecasting under real deregulated electric market and electricity MCP forecasting under deregulated electric market with perfect competition. The PJM interconnect system has been utilized for numerical results. Techniques have been developed to overcome difficulties in training the neural network and improve the training results.

In previous research on pricing mortality-linked securities, the no-arbitrage approach is often used. However, this method, which takes market prices as given, is difficult to implement in today's embryonic market where there are few traded securities. In particular, with limited market price data, identifying a risk neutral measure requires strong assumptions. In this thesis, we approach the pricing problem from a different angle by considering economic methods. We propose pricing approaches in both competitive market and non-competitive market. In the competitive market, we treat the pricing work as a Walrasian tâtonnement process, in which prices are determined through a gradual calibration of supply and demand. Such a pricing framework provides with us a pair of supply and demand curves. From these curves we can tell if there will be any trade between the counterparties, and if there will, at what price the mortality-linked security will be traded. This method does not require the market prices of other mortality-linked securities as input. This can spare us from the problems associated with the lack of market price data. We extend the pricing framework to incorporate population basis risk, which arises when a pension plan relies on standardized instruments to hedge its longevity risk exposure. This extension allows us to obtain the price and trading quantity of mortality-linked securities in the presence of population basis risk. The resulting supply and demand curves help us understand how population basis risk would affect the behaviors of agents. We apply the method to a hypothetical longevity bond, using real mortality data from different populations. Our illustrations show that, interestingly, population basis risk can affect the price of a mortality-linked security in different directions, depending on the properties of the populations involved. We have also examined the impact of transitory mortality jumps on trading in a competitive market. Mortality dynamics are subject to jumps, which are due to events such as the Spanish flu in 1918. Such jumps can have a significant impact on prices of mortality-linked securities, and therefore should be taken into account in modeling. Although several single-population mortality models with jump effects have been developed, they are not adequate for trades in which population basis risk exists. We first develop a two-population mortality model with transitory jump effects, and then we use the proposed mortality model to examine how mortality jumps may affect the supply and demand of mortality-linked securities. Finally, we model the pricing process in a non-competitive market as a bargaining game. Nash's bargaining solution is applied to obtain a unique trading contract. With no requirement of a competitive market, this approach is more appropriate for the current mortality-linked security market. We compare this approach with the other proposed pricing method. It is found that both pricing methods lead to Pareto optimal outcomes.

No / Organisational learning is often presented as one way in which firms may respond to increasingly competitive market conditions by managing their knowledge assets in more effective ways. Although theoretically and conceptually plausible, there is limited empirical evidence, particularly from smaller firms, in support of this view. This study aims to provide some evidence that links organisational learning and performance. Extant theory suggests that organisational learning may range from a passive orientation (working within a current paradigm) to an active orientation (questioning a current paradigm) at both the individual and the collective levels. This study examines the learning orientations of 300 smaller manufacturing and service firms in terms of an active¿passive learning construct. The results suggest that higher-growth manufacturing firms have a more active learning orientation. These firms make greater use of knowledge assets than do their lower growth counterparts, and this may have important implications for the management of learning in smaller manufacturing firms.

Purpose - Previous studies suggest that regulatory changes result in an increased audit effort. Given a competitive market setting and audit price negotiation between the auditor and the auditee, it is unclear if an increased audit effort results in higher audit prices. The purpose of this study is to provide the reader with a deeper understanding concerning pricing of audit services. Moreover, we examine if the EU audit reform package, comprising of Directive 2014/56/EU and Regulation (EU) No 537/2014, has had an impact on audit prices. Method - This study was conducted through semi-structured interviews with public authorized accountants from Big 4-firms in order to gain a deeper insight in audit pricing and the EU audit reform. Results - The results in this study show that audit effort has increased as a result of the EU audit reform. In addition, this study provides some support that the increase in audit effort has resulted in higher audit prices. Conclusion - Our main conclusion in this study is that the EU audit reform has resulted in higher audit prices, despite indications that an increased audit effort does not necessarily result in higher audit prices. The main reason behind this uncertainty is due to factors such as the competitive market setting and price negotiation. / Syfte - Tidigare studier indikerar att regelverksförändringar resulterar i en ökad resursåtgång för revisorer. Givet att det råder konkurrens på revisionsmarknaden och att prisförhandlingar sker mellan revisorer och kunder, innebär det oklarheter om en ökad resursåtgång leder till en högre prissättning av revisionstjänster. Syftet med denna studie är att bidra med en djupare förståelse kring prissättning av revisionstjänster. Vidare undersöker viom EU:s revisionspaket, bestående av Direktiv 2014/56/EU och Förordning (EU) Nr 537/2014, har haft en inverkan på prissättningen. Metod - Denna studie utfördes genom semistrukturerade intervjuer med auktoriserade revisorer tillhörande Big 4-byråer, för att få en djupare insikt i prissättning av revisionstjänster samt EU:s revisionspaket. Resultat - Resultatet i denna studie visar att resursåtgången för revisorer har ökat som ett resultat av EU:s revisionspaket. Vidare ger denna studie ett visst stöd att ökningen i resursåtgång har lett till en ökad prissättning av revisionstjänster. Slutsats - Vår huvudsakliga slutsats i denna studie är att EU:s revisionspaket har resulterat i en högre prissättning av revisionstjänster, trots att en ökad resursåtgång inte entydigt leder till ökade revisionspriser. Anledningen till denna tvetydighet beror på osäkerhetsfaktorer såsom den konkurrensmässiga marknadssituationen och prisförhandling.

"The strategic analystis of Czech post s.p." is a topic of my thesis.The aim of this work was review the present situation of Czech post s.p. and to propose strategy for preserve of domination logistic position operator on market.I have used method of Internal analysis and external environment for synthesis and analysis.On the survey for find out the result was used a nut for servey internal and external factors.For proposal of strategy was internal external nut.Czech post s.p. has dominantly position on logistic market and it should use its competitive advantages to prepare for get quality sardonic partner,who would aid to extend current and new products in the present position in the competitive market.

Tato diplomová práce je zaměřena na vývoj marketingové strategie pro zavedení produktů na vysoce konkurečním trhu zdravotnických prostředků. Konkrétně se zaměřuje na zavedení ablačního katetru a mapovacího zařízení pro léčbu srdečních chorob, které vyrábí americká společnost St. Jude Medical. Práce popisuje zavedení na trh, aby bylo možné najít kritické body a optimalizovat celý tento proces.

Two optimisation problems were considered, in which market exposure is indirectly controlled. The first one models the capital of a company and an independent portfolio of new businesses, each one represented by a Cram\'r-Lundberg process. The company can choose the proportion of new business it wants to take on and can alter this proportion over time. Here the objective is to find a strategy that maximises the survival probability. We use a point processes framework to deal with the impact of an adapted strategy in the intensity of the new business. We prove that when Cram\'{e}r-Lundberg processes with exponentially distributed claims, it is optimal to choose a threshold type strategy, where the company switches between owning all new businesses or none depending on the capital level. For this type of processes that change both drift and jump measure when crossing the constant threshold, we solve the one and two-sided exit problems. This optimisation problem is also solved when the capital of the company and the new business are modelled by spectrally positive L\'vy processes of bounded variation. Here the one-sided exit problem is solved and we prove optimality of the same type of threshold strategy for any jump distribution. The second problem is a stochastic variation of the work done by Taylor about underwriting in a competitive market. Taylor maximised discounted future cash flows over a finite time horizon in a discrete time setting when the change of exposure from one period to the next has a multiplicative form involving the company's premium and the market average premium. The control is the company's premium strategy over a the mentioned finite time horizon. Taylor's work opened a rich line of research, and we discuss some of it. In contrast with Taylor's model, we consider the market average premium to be a Markov chain instead of a deterministic vector. This allows to model uncertainty in future conditions of the market. We also consider an infinite time horizon instead of finite. This solves the time dependency in Taylor's optimal strategies that were giving unrealistic results. Our main result is a formula to calculate explicitly the value function of a specific class of pricing strategies. Further we explore concrete examples numerically. We find a mix of optimal strategies where in some examples the company should follow the market while in other cases should go against it.