Decision Support Tools (DSTs) are commonly utilised within the Asset Management (AM) operations of infrastructure organisations. These manual or computerised tools are used to support decisions about what assets to acquire and how to operate them. Their performance can therefore have significant financial and non-financial implications for a business. Despite their importance, managing the performance of DSTs after implementation has received only limited attention within the literature. The output of this research is a conceptual approach for managing the performance of decision support tools used within an Asset Management context. It encompasses a risk-based DST Performance Management Process and DST Performance Assessment Techniques (the methods for applying the process in an industry setting).The novelty of the approach: (1) Alignment with the fundamental principles of the International Standard for Asset Management, ISO 5500x:2014. Thus, consistency of the management of DSTs with other assets types. (2) A generic process that is tailored to the context of the specific organisation. (3) Consistency with the risk management process (ISO 31000:2009) and meeting the requirements for a quality process defined within the Quality Management Standard (ISO 9000: 2015). (4) A cyclical process design ensuring that the approach, and how the approach is applied within an industry setting, will evolve to reflect the changing environment. A case study and the input of subject matter experts from within National Grid Electricity Transmission was used to both inform and evaluate the conceptual approach design. A semi-structured interview, with a water sector subject matter expert, assesses the transferability of the approach to a wider Asset Management population. The results of the evaluation demonstrate the conceptual approach to be both logical and useable in each context. The future research pathway looks to progress the conceptual approach through to industry adoption.

Statistical mechanics pursues low-dimensional descriptions of systems with a very large number of degrees of freedom. I explore this theme in two contexts. The main body of this dissertation explores and extends the Yard Sale Model (YSM) of economic transactions using a combination of simulations and theory. The YSM is a simple interacting model for wealth distributions which has the potential to explain the empirical observation of Pareto distributions of wealth. I develop the link between wealth condensation and the breakdown of ergodicity due to nonlinear diffusion effects which are analogous to the geometric random walk. Using this, I develop a deterministic effective theory of wealth transfer in the YSM that is useful for explaining many quantitative results. I introduce various forms of growth to the model, paying attention to the effect of growth on wealth condensation, inequality, and ergodicity. Arithmetic growth is found to partially break condensation, and geometric growth is found to completely break condensation. Further generalizations of geometric growth with growth in- equality show that the system is divided into two phases by a tipping point in the inequality parameter. The tipping point marks the line between systems which are ergodic and systems which exhibit wealth condensation. I explore generalizations of the YSM transaction scheme to arbitrary betting functions to develop notions of universality in YSM-like models. I find that wealth condensation is universal to a large class of models which can be divided into two phases. The first exhibits slow, power-law condensation dynamics, and the second exhibits fast, finite-time condensation dynamics. I find that the YSM, which exhibits exponential dynamics, is the critical, self-similar model which marks the dividing line between the two phases. The final chapter develops a low-dimensional approach to materials microstructure quantification. Modern materials design harnesses complex microstructure effects to develop high-performance materials, but general microstructure quantification is an unsolved problem. Motivated by statistical physics, I envision microstructure as a low-dimensional manifold, and construct this manifold by leveraging multiple machine learning approaches including transfer learning, dimensionality reduction, and computer vision breakthroughs with convolutional neural networks.

<p>Sammanfattning</p><p>Flygmarknaden är en marknad som på senare år har genomgått, och fortfarande genomgår, stora förändringar. Från att ha varit monopolistiskt och hårt reglerad har den successivt luckrats upp. Detta har lett till ökad konkurrens, större osäkerhet och minskad stabilitet. Förutsättningarna för ett flygbolag att kunna starta upp och bedriva sin verksamhet är hårda. För att kunna möta dessa svårigheter måste ett flygbolag lägga upp strategier som tar dessa i beaktande. Ett sätt att vinna fördelar är att välja att leasa flygplan istället för att enbart köpa flygplan själv. Det vi ämnar svara på med uppsatsen är:</p><p>Vilka är anledningarna till att leasing används i den kommersiella reguljärt trafikerande flygbranschen?</p><p>Då utgångspunkten för uppsatsen är att få en större förståelse och bättre bild av valet att leasa än en generaliserbar kunskap, har vi gjort en kvalitativ ansats. Den kvalitativa undersökningen är gjord med hjälp av semistrukturerade intervjuer för att få större bredd på svaren. Målgruppen är de svenska flygbolagen, och det finns två kriterier för att flygbolagen ska räknas som ”ett svenskt bolag med reguljärtrafik”:</p><p>1) de ska trafikera en inrikessträcka</p><p>2) de ska ha tillstånd att flyga i Sverige</p><p>Ett ändamålsenligt urval användes och vi ringde upp alla flygbolag som stämde in på kriterierna. Sammanlagt deltog nio flygbolag av fjorton i undersökningen. Dessa leasade alltifrån alla flygplan till att inte leasa några. Dessutom inkluderades en leasegivare, för att vi skulle kunna se allt ur ett annat perspektiv.</p><p>Den teoretiska referensramen består av två kapitel: Leasing och Leasing på flygmarknaden.</p><p>Leasingkapitlet behandlar de olika leasingmetoderna och hur dessa, beroende på vilken leasingvariant man använder, kan anpassas efter flygbolagets behov. Leasing på flygmarknaden beskriver hur marknaden ser ut och vilka förutsättningar ett flygbolag måste övervinna. Lågkonjunkturer och kapitalbrist är några av de hinder ett flygbolag har, som kan sägas komma av den avreglering som påbörjades på 70-talet i USA. Att leasa är för många flygbolag en del av strategin för att kunna hantera exempelvis konjunkturnedgångar. Detta berörs i kapitel fyra.</p><p>Det empiriska materialet och analysen visar att många svenska flygbolag kan delas in i två kategorier när det kommer till leasing: de som har kapital och de som inte har det. För dem som inte har kapital är leasing ett sätt att kunna starta upp ändå, medan de som har kapital ser leasing ur en strategisk synvinkel. Genom att ha leasade flygplan i sin flygflotta kan ett flygbolag få hjälp att möta konjunkturnedgångar, starta upp nya sträckor, att inte binda upp kapital. Genom att inte behöva sköta om flygplanen och ha mycket kapital till hands kan flygbolagen satsa på sin kärnverksamhet, att flyga.</p>

Sammanfattning Flygmarknaden är en marknad som på senare år har genomgått, och fortfarande genomgår, stora förändringar. Från att ha varit monopolistiskt och hårt reglerad har den successivt luckrats upp. Detta har lett till ökad konkurrens, större osäkerhet och minskad stabilitet. Förutsättningarna för ett flygbolag att kunna starta upp och bedriva sin verksamhet är hårda. För att kunna möta dessa svårigheter måste ett flygbolag lägga upp strategier som tar dessa i beaktande. Ett sätt att vinna fördelar är att välja att leasa flygplan istället för att enbart köpa flygplan själv. Det vi ämnar svara på med uppsatsen är: Vilka är anledningarna till att leasing används i den kommersiella reguljärt trafikerande flygbranschen? Då utgångspunkten för uppsatsen är att få en större förståelse och bättre bild av valet att leasa än en generaliserbar kunskap, har vi gjort en kvalitativ ansats. Den kvalitativa undersökningen är gjord med hjälp av semistrukturerade intervjuer för att få större bredd på svaren. Målgruppen är de svenska flygbolagen, och det finns två kriterier för att flygbolagen ska räknas som ”ett svenskt bolag med reguljärtrafik”: 1) de ska trafikera en inrikessträcka 2) de ska ha tillstånd att flyga i Sverige Ett ändamålsenligt urval användes och vi ringde upp alla flygbolag som stämde in på kriterierna. Sammanlagt deltog nio flygbolag av fjorton i undersökningen. Dessa leasade alltifrån alla flygplan till att inte leasa några. Dessutom inkluderades en leasegivare, för att vi skulle kunna se allt ur ett annat perspektiv. Den teoretiska referensramen består av två kapitel: Leasing och Leasing på flygmarknaden. Leasingkapitlet behandlar de olika leasingmetoderna och hur dessa, beroende på vilken leasingvariant man använder, kan anpassas efter flygbolagets behov. Leasing på flygmarknaden beskriver hur marknaden ser ut och vilka förutsättningar ett flygbolag måste övervinna. Lågkonjunkturer och kapitalbrist är några av de hinder ett flygbolag har, som kan sägas komma av den avreglering som påbörjades på 70-talet i USA. Att leasa är för många flygbolag en del av strategin för att kunna hantera exempelvis konjunkturnedgångar. Detta berörs i kapitel fyra. Det empiriska materialet och analysen visar att många svenska flygbolag kan delas in i två kategorier när det kommer till leasing: de som har kapital och de som inte har det. För dem som inte har kapital är leasing ett sätt att kunna starta upp ändå, medan de som har kapital ser leasing ur en strategisk synvinkel. Genom att ha leasade flygplan i sin flygflotta kan ett flygbolag få hjälp att möta konjunkturnedgångar, starta upp nya sträckor, att inte binda upp kapital. Genom att inte behöva sköta om flygplanen och ha mycket kapital till hands kan flygbolagen satsa på sin kärnverksamhet, att flyga.

While some prior studies document that investors overreact to information in sales growth as consistent with representativeness bias, other studies find no evidence of investor overreaction to either sales or earnings growth. Other recent studies also show that sales growth does not predict stock returns after controlling for changes in outstanding shares and asset growth. I reexamine the role of representativeness by investigating whether the effects of this bias are confounded by the presence of another effect that has been extensively documented - investors' underreaction to fundamentals. Adjusting for investor under-reaction to fundamentals, I document strong evidence that investors overreact to sales growth as predicted under representativeness despite adding accruals, asset growth, and equity issuance as additional controls. In cross-sectional regressions of future stock returns on predictive variables that control for fundamentals, changes in equity shares, accruals, and lagged 36 month returns, I find that the coefficient on sales growth is highly significant over both the full sample period 1970-2009 (t-stat -3.12). Furthermore, asset growth, equity issuance, and accruals lose much of their significance in favor of sales growth. I also provide evidence that rejects a theory based on fixation in favor of representativeness. These results document evidence of overreaction to past sales growth in firms where underreaction to fundamentals does not confound the overreaction due to representativeness bias.

This thesis studies information in financial markets from three perspectives: the role of information asymmetry in alleviating dividend payers’ seasoned equity offering (SEO) announcement returns, the leading behavior of equity analysts who collect and process information, and the pricing of productivity-related information. More specifically, Chapter 1 studies whether the market reacts less negatively to dividend payers’ SEO announcements. Using US data from 1975 to 2002, I find that prior to SEO announcement dates, dividend payers have less information asymmetries than non-dividend payers. This difference was not large before the mid-1980s, but increased dramatically since then. This finding, together with the disappearing dividend puzzle documented in Fama and French (2001), suggests that a firm’s dividend status was not an important signal for SEOs prior to the mid-1980s, but became important since then. The market reacts less negatively to dividend payers’ SEO announcements since the mid-1980s. Chapter 2 studies equity analysts’ leading behavior in equity recommendations. I develop a measure of leading recommendations based on the observation that other recommendations move towards those of the leader. I find that analysts who are more likely to lead are past leaders, past All-American stars, analysts from large brokerage houses, and analysts with fewer recommendations. I find that the market reacts more strongly to recommendations of leaders and leaders are less likely to be terminated from their jobs. Chapter 3 examines the link between productivity and the cross-section of security returns. The CAPM and CCAPM have had problems finding empirical validations. In contrast, by creating factor mimicking portfolios with respect to productivity, I introduce a stock market factor that mimics the driving force behind the CCAPM. First, I find that the productivity factor affects the overall market return and that on average it contributes 0.75 to 2.41 percent annually, for the range of productivity factors I construct. Further, I show that productivity is priced even when the market excess return and factors based on size and book-to-market are included in standard asset pricing tests. However, the market excess return and the book-to-market factor still explain asset returns.

Deregulated and competitive power market places utilities under high pressure to assure providing power with a satisfactory level of power continuity. This objective entails a high level of reliability which in turn demands a high financial budget for design, operation, and maintenance. Therefore, the need for utilities to balance these factors has been increasing to become the core of a utility's asset management activities. Maintenance is a key aspect of asset management. The main objective of maintenance is to extend the lifetime of equipment and/or reduce the probability of failure. Maintenance activities play an important role in improving system reliability by keeping the condition of a system's equipment within an acceptable level. Generally speaking, technical requirements and budget constraints are the most influential factors in assigning maintenance activities. The most cost-effective maintenance approach is the approach that can sustain a high level of reliability while maintenance cost is minimized. The transformer has a significant role in the power system due to its remarkable effect on the overall level of reliability in addition to its extensive investments in the power grid. Transformer management is comprised of identifying the appropriate type and frequency to maintain the transformer, and the appropriate time to replace the transformer in a cost-effective manner. The essential objective of this thesis is to introduce a novel framework for transformer management. An approach which links maintenance and replacement decisions is presented in this thesis. This approach proposes a methodical decision-making system to determine the optimal time to replace the transformer. Indeed, the proposed approach essentially investigates the cost-effectiveness of replacing the transformer both before and after the lifetime is extended by maintenance. To properly investigate the effect of maintenance, maintenance activities should first be scheduled effectively. Therefore, this approach introduces a maintenance strategy based on reliability-centered maintenance (RCM) concept and genetic algorithm (GA) to optimally schedule maintenance activities. Two replacement studies are conducted: with and without the effect of maintenance. A comparison between replacement studies is discussed in the proposed approach.

Infrastructure deterioration models are an integral part of asset management. Deterioration models are used to predict future asset condition and to estimate funding requirements. The purpose of this research is to develop a framework to create infrastructure deterioration models. An overview of the various types of deterioration models is included, presenting the advantages and disadvantages of each type. Existing deterioration model frameworks are also considered. A deterioration modelling framework is then proposed. The selection of the model type, calibration and validation is presented. The framework is then applied to two case studies. The first case study involves a comparison of three pavement deterioration models, created for the City of Oshawa for use in their asset management system. The second case study involves modelling sewer deterioration. This model has been developed to explore the relationship between age, material and deterioration in trunk sewers.

Infrastructure deterioration models are an integral part of asset management. Deterioration models are used to predict future asset condition and to estimate funding requirements. The purpose of this research is to develop a framework to create infrastructure deterioration models. An overview of the various types of deterioration models is included, presenting the advantages and disadvantages of each type. Existing deterioration model frameworks are also considered. A deterioration modelling framework is then proposed. The selection of the model type, calibration and validation is presented. The framework is then applied to two case studies. The first case study involves a comparison of three pavement deterioration models, created for the City of Oshawa for use in their asset management system. The second case study involves modelling sewer deterioration. This model has been developed to explore the relationship between age, material and deterioration in trunk sewers.

This thesis studies information in financial markets from three perspectives: the role of information asymmetry in alleviating dividend payers’ seasoned equity offering (SEO) announcement returns, the leading behavior of equity analysts who collect and process information, and the pricing of productivity-related information. More specifically, Chapter 1 studies whether the market reacts less negatively to dividend payers’ SEO announcements. Using US data from 1975 to 2002, I find that prior to SEO announcement dates, dividend payers have less information asymmetries than non-dividend payers. This difference was not large before the mid-1980s, but increased dramatically since then. This finding, together with the disappearing dividend puzzle documented in Fama and French (2001), suggests that a firm’s dividend status was not an important signal for SEOs prior to the mid-1980s, but became important since then. The market reacts less negatively to dividend payers’ SEO announcements since the mid-1980s. Chapter 2 studies equity analysts’ leading behavior in equity recommendations. I develop a measure of leading recommendations based on the observation that other recommendations move towards those of the leader. I find that analysts who are more likely to lead are past leaders, past All-American stars, analysts from large brokerage houses, and analysts with fewer recommendations. I find that the market reacts more strongly to recommendations of leaders and leaders are less likely to be terminated from their jobs. Chapter 3 examines the link between productivity and the cross-section of security returns. The CAPM and CCAPM have had problems finding empirical validations. In contrast, by creating factor mimicking portfolios with respect to productivity, I introduce a stock market factor that mimics the driving force behind the CCAPM. First, I find that the productivity factor affects the overall market return and that on average it contributes 0.75 to 2.41 percent annually, for the range of productivity factors I construct. Further, I show that productivity is priced even when the market excess return and factors based on size and book-to-market are included in standard asset pricing tests. However, the market excess return and the book-to-market factor still explain asset returns.