Uncertainty Management in Acquisitions: What Scenario Analysis Could Offer

This study answers to How scenario analysis could help acquiring companies to reduce uncertainty in the acquisition process? It is due to the mismatch between academic world’s caveat emptor and business world’s eagerness to pursue acquisitions that motivated this study. Acquisitions are as popular as ever, thus, managing the uncertainty surrounding these transactions is relevant. This study creates a generic theoretical model with a strategy-level scope. Thus, the study does not discuss nor does it seek answers to operational issues related in both fields. This study is explorative and constructivist in nature. It discusses briefly the concepts and relatedness of risk and uncertainty and establishes a hierarchy between these two: Risks being a “sub-section” of uncertainty, although not with clear boundaries. Acquisition theory follows the process view that understands acquisitions as a process with various levels – some strategic, some operational. Scenario analysis is presented as tool for management to enrich their strategic discussion and understand their future options. The empirical data collection is done through interviewing. The results are reflected on literature on strategic management, scenario literature, and on a consultancy’s report picturing firm’s strategies in accordance with their acquisition processes. The study has an abductive approach as it tries to combine multiple views and generates discussion between literature review, interviews, the report, and second round of literature. The model suggests three propositions: First, at the strategic decision making level, when the decision whether or not to pursue an acquisition growth strategy has been made, it provides firms new data and enriches the strategic discussion. Second, when the acquisition strategy has been created, it can be applied as a tool to measure possible acquisition targets against the backdrop of the first set of scenarios. Third, due to the scenario analysis’ requirement to include people with various backgrounds and from multiple levels of the corporate hierarchy, it could help managers to avoid biases stemming from hubris.

Using an end-of-life care pathway in acute stroke: a mixed methods study of decision-making and care experiences

Background: The evidence base on end-of-life care in acute stroke is limited, particularly with regard to recognising dying and related decision-making. There is also limited evidence to support the use of end-of-life care pathways (standardised care plans) for patients who are dying after stroke. Aim: This study aimed to explore the clinical decision-making involved in placing patients on an end-of-life care pathway, evaluate predictors of care pathway use, and investigate the role of families in decision-making. The study also aimed to examine experiences of end-of-life care pathway use for stroke patients, their relatives and the multi-disciplinary health care team. Methods: A mixed methods design was adopted. Data were collected in four Scottish acute stroke units. Case-notes were identified prospectively from 100 consecutive stroke deaths and reviewed. Multivariate analysis was performed on case-note data. Semi-structured interviews were conducted with 17 relatives of stroke decedents and 23 healthcare professionals, using a modified grounded theory approach to collect and analyse data. The VOICES survey tool was also administered to the bereaved relatives and data were analysed using descriptive statistics and thematic analysis of free-text responses. Results: Relatives often played an important role in influencing aspects of end-of-life care, including decisions to use an end-of-life care pathway. Some relatives experienced enduring distress with their perceived responsibility for care decisions. Relatives felt unprepared for and were distressed by prolonged dying processes, which were often associated with severe dysphagia. Pro-active information-giving by staff was reported as supportive by relatives. Healthcare professionals generally avoided discussing place of care with families. Decisions to use an end-of-life care pathway were not predicted by patients’ demographic characteristics; decisions were generally made in consultation with families and the extended health care team, and were made within regular working hours. Conclusion: Distressing stroke-related issues were more prominent in participants’ accounts than concerns with the end-of-life care pathway used. Relatives sometimes perceived themselves as responsible for important clinical decisions. Witnessing prolonged dying processes was difficult for healthcare professionals and families, particularly in relation to the management of persistent major swallowing difficulties.

Correlations among behavior, performance and environment in broiler breeders using multivariate analysis

Animal welfare issues have received much attention not only to supply farmed animal requirements, but also to ethical and cultural public concerns. Daily collected information, as well as the systematic follow-up of production stages, produces important statistical data for production assessment and control, as well as for improvement possibilities. In this scenario, this research study analyzed behavioral, production, and environmental data using Main Component Multivariable Analysis, which correlated observed behaviors, recorded using video cameras and electronic identification, with performance parameters of female broiler breeders. The aim was to start building a system to support decision-making in broiler breeder housing, based on bird behavioral parameters. Birds were housed in an environmental chamber, with three pens with different controlled environments. Bird sensitivity to environmental conditions were indicated by their behaviors, stressing the importance of behavioral observations for modern poultry management. A strong association between performance parameters and the behavior at the nest, suggesting that this behavior may be used to predict productivity. The behaviors of ruffling feathers, opening wings, preening, and at the drinker were negatively correlated with environmental temperature, suggesting that the increase of in the frequency of these behaviors indicate improvement of thermal welfare.

Performance analysis of brazilian public and philanthropic hospitals

This paper presents the results of a research that aimed at identifying optimal performance standards of Brazilian public and philanthropic hospitals. In order to carry out the analysis, a model based on Data Envelopment Analysis (DEA) was developed. We collected financial data from hospitals’ financial statements available on the internet, as well as operational data from the Information Technology Department of the Brazilian Public Health Care System – SUS (DATASUS). Data from 18 hospitals from 2007 to 2011 were analyzed. Our DEA model used both operational and financial indicators (variables). In order to develop this model, two indicators were considered inputs: Values (in Brazilian Reais) of Fixed Assets and Planned Capacity. On the other hand, the following indicators were considered outputs: Net Margin, Return on Assets and Institutional Mortality Rate. As regards the proposed model, there were five hospitals with optimal performance and four hospitals were considered inefficient, upon the analysis of the variables, considering the analyzed period. Analysis of the weights indicated the most relevant variables for determining efficiency and scale variable values, which is an important tool to aid the decision-making by hospital managers. Finally, the scale variables determined the returns on production, indicating that 14 hospitals work with scale diseconomies. This may indicate inefficiency in the resource management of the Brazilian public health-care system, by analyzing this set of proposed variables.

Export and import market-specific characteristics. How they drive the decision to trade and how much

Using a rich firm-level dataset on the Italian manufacturing industry, this paper provides a comprehensive analysis of the role that firms and market characteristics play in shaping firms’ trade activities. We enhance the previous analyses by considering firms’ engagement in international transactions, by focusing on either exports or imports. We show that the determinants of a firm’s export participation and value across countries also drive import behavior. Our research is consistent with the presence of country-specific sunk costs and with a qualitatively similar role of gravity forces and other country attributes on both sides of trading activities. Our evidence, however, militates in favor of a framework where variations in market characteristics have a larger impact on imports than exports.

Uma metodologia para a análise do desempenho sustentável dos postos de revenda de combustível na cidade de Natal/RN, com o uso de data envelopment analysis-DEA

The increasing use of fossil fuels in line with cities demographic explosion carries out to huge environmental impact in society. For mitigate these social impacts, regulatory requirements have positively influenced the environmental consciousness of society, as well as, the strategic behavior of businesses. Along with this environmental awareness, the regulatory organs have conquered and formulated new laws to control potentially polluting activities, mostly in the gas stations sector. Seeking for increasing market competitiveness, this sector needs to quickly respond to internal and external pressures, adapting to the new standards required in a strategic way to get the Green Badge . Gas stations have incorporated new strategies to attract and retain new customers whom present increasingly social demand. In the social dimension, these projects help the local economy by generating jobs and income distribution. In this survey, the present research aims to align the social, economic and environmental dimensions to set the sustainable performance indicators at Gas Stations sector in the city of Natal/RN. The Sustainable Balanced Scorecard (SBSC) framework was create with a set of indicators for mapping the production process of gas stations. This mapping aimed at identifying operational inefficiencies through multidimensional indicators. To carry out this research, was developed a system for evaluating the sustainability performance with application of Data Envelopment Analysis (DEA) through a quantitative method approach to detect system s efficiency level. In order to understand the systemic complexity, sub organizational processes were analyzed by the technique Network Data Envelopment Analysis (NDEA) figuring their micro activities to identify and diagnose the real causes of overall inefficiency. The sample size comprised 33 Gas stations and the conceptual model included 15 indicators distributed in the three dimensions of sustainability: social, environmental and economic. These three dimensions were measured by means of classical models DEA-CCR input oriented. To unify performance score of individual dimensions, was designed a unique grouping index based upon two means: arithmetic and weighted. After this, another analysis was performed to measure the four perspectives of SBSC: learning and growth, internal processes, customers, and financial, unifying, by averaging the performance scores. NDEA results showed that no company was assessed with excellence in sustainability performance. Some NDEA higher efficiency Gas Stations proved to be inefficient under certain perspectives of SBSC. In the sequence, a comparative sustainable performance and assessment analyzes among the gas station was done, enabling entrepreneurs evaluate their performance in the market competitors. Diagnoses were also obtained to support the decision making of entrepreneurs in improving the management of organizational resources and promote guidelines the regulators. Finally, the average index of sustainable performance was 69.42%, representing the efforts of the environmental suitability of the Gas station. This results point out a significant awareness of this segment, but it still needs further action to enhance sustainability in the long term

Network Construction and Graph Theoretical Analysis of Functional Language Networks in Pediatric Epilepsy

This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ the whole brain network to perform the ADDT language task; on the contrary, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was carried out. The analysis revealed no substantial global network feature differences between the patient and control groups. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient’s extent of activation network showed a tendency towards more random networks. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. The left hemispheric hubs displayed greater centrality values for patients, whereas the right hemispheric hubs displayed greater centrality values for controls. This hub hemispheric disparity was not correlated with a right atypical language laterality found in six patients. Finally it was shown that a multi-level unsupervised clustering scheme based on self-organizing maps, a type of artificial neural network, and k-means was able to fairly and blindly separate the subjects into their respective patient or control groups. The clustering was initiated using the local nodal centrality measurements only. Compared to the extent of activation network, the intensity of activation network clustering demonstrated better precision. This outcome supports the assertion that the local centrality differences presented by the intensity of activation network can be associated with focal epilepsy.

Irish state infrastructural investment: an analysis of past patterns, and an outline of a future integrated systems of systems evaluation methodology

The literature clearly links the quality and capacity of a country’s infrastructure to its economic growth and competitiveness. This thesis analyses the historic national and spatial distribution of investment by the Irish state in its physical networks (water, wastewater and roads) across the 34 local authorities and examines how Ireland is perceived internationally relative to its economic counterparts. An appraisal of the current status and shortcomings of Ireland’s infrastructure is undertaken using key stakeholders from foreign direct investment companies and national policymakers to identify Ireland's infrastructural gaps, along with current challenges in how the country is delivering infrastructure. The output of these interviews identified many issues with how infrastructure decision-making is currently undertaken. This led to an evaluation of how other countries are informing decision-making, and thus this thesis presents a framework of how and why Ireland should embrace a Systems of Systems (SoS) methodology approach to infrastructure decision-making going forward. In undertaking this study a number of other infrastructure challenges were identified: significant political interference in infrastructure decision-making and delivery the need for a national agency to remove the existing ‘silo’ type of mentality to infrastructure delivery how tax incentives can interfere with the market; and their significance. The two key infrastructure gaps identified during the interview process were: the need for government intervention in the rollout of sufficient communication capacity and at a competitive cost outside of Dublin; and the urgent need to address water quality and capacity with approximately 25% of the population currently being served by water of unacceptable quality. Despite considerable investment in its national infrastructure, Ireland’s infrastructure performance continues to trail behind its economic partners in the Eurozone and OECD. Ireland is projected to have the highest growth rate in the euro zone region in 2015 and 2016, albeit that it required a bailout in 2010, and, at the time of writing, is beginning to invest in its infrastructure networks again. This thesis proposes the development and implementation of a SoS approach for infrastructure decision-making which would be based on: existing spatial and capacity data of each of the constituent infrastructure networks; and scenario computation and analysis of alternative drivers eg. Demographic change, economic variability and demand/capacity constraints. The output from such an analysis would provide valuable evidence upon which policy makers and decision makers alike could rely, which has been lacking in historic investment decisions.

Enabling effective operational decision making on a Combined Heat and Power System using the 5C architecture

The use of Cyber Physical Systems (CPS) to optimise industrial energy systems is an approach which has the potential to positively impact on manufacturing sector energy efficiency. The need to obtain data to facilitate the implementation of a CPS in an industrial energy system is however a complex task which is often implemented in a non-standardised way. The use of the 5C CPS architecture has the potential to standardise this approach. This paper describes a case study where data from a Combined Heat and Power (CHP) system located in a large manufacturing company was fused with grid electricity and gas models as well as a maintenance cost model using the 5C architecture with a view to making effective decisions on its cost efficient operation. A control change implemented based on the cognitive analysis enabled via the 5C architecture implementation has resulted in energy cost savings of over €7400 over a four-month period, with energy cost savings of over €150,000 projected once the 5C architecture is extended into the production environment.

A Microdata Analysis Approach to Transport Infrastructure Maintenance

Maintenance of transport infrastructure assets is widely advocated as the key in minimizing current and future costs of the transportation network. While effective maintenance decisions are often a result of engineering skills and practical knowledge, efficient decisions must also account for the net result over an asset's life-cycle. One essential aspect in the long term perspective of transport infrastructure maintenance is to proactively estimate maintenance needs. In dealing with immediate maintenance actions, support tools that can prioritize potential maintenance candidates are important to obtain an efficient maintenance strategy. This dissertation consists of five individual research papers presenting a microdata analysis approach to transport infrastructure maintenance. Microdata analysis is a multidisciplinary field in which large quantities of data is collected, analyzed, and interpreted to improve decision-making. Increased access to transport infrastructure data enables a deeper understanding of causal effects and a possibility to make predictions of future outcomes. The microdata analysis approach covers the complete process from data collection to actual decisions and is therefore well suited for the task of improving efficiency in transport infrastructure maintenance. Statistical modeling was the selected analysis method in this dissertation and provided solutions to the different problems presented in each of the five papers. In Paper I, a time-to-event model was used to estimate remaining road pavement lifetimes in Sweden. In Paper II, an extension of the model in Paper I assessed the impact of latent variables on road lifetimes; displaying the sections in a road network that are weaker due to e.g. subsoil conditions or undetected heavy traffic. The study in Paper III incorporated a probabilistic parametric distribution as a representation of road lifetimes into an equation for the marginal cost of road wear. Differentiated road wear marginal costs for heavy and light vehicles are an important information basis for decisions regarding vehicle miles traveled (VMT) taxation policies. In Paper IV, a distribution based clustering method was used to distinguish between road segments that are deteriorating and road segments that have a stationary road condition. Within railway networks, temporary speed restrictions are often imposed because of maintenance and must be addressed in order to keep punctuality. The study in Paper V evaluated the empirical effect on running time of speed restrictions on a Norwegian railway line using a generalized linear mixed model.

Load Profile Analysis Tool for Electrical Appliances in Households

This paper presents a methodology to forecast the hourly and daily consumption in households. The methodology was validated for households in Lisbon region, Portugal. The paper shows that the forecast tool allows obtaining satisfactory results for forecasting. Models of demand response allow the support of consumer’s decision in exchange for an economic benefit by the redefinition of load profile or changing the appliance consumption period. It is also in the interest of electric utilities to take advantage of these changes, particularly when consumers have an action on the demand-side management or production. Producers need to understand the load profile of households that are connected to a smart grid, to promote a better use of energy, as well as optimize the use of micro-generation from renewable sources, not only to delivering to the network but also in self-consumption.

Analysis of Dyscalculia Evidences through Artificial Intelligence Systems

Dyscalculia is usually perceived of as a specific learning difficulty for mathematics or, more appropriately, arithmetic. Because definitions and diagnoses of dyscalculia are in their infancy and sometimes are contradictory. However, mathematical learning difficulties are certainly not in their infancy and are very prevalent and often devastating in their impact. Co-occurrence of learning disorders appears to be the rule rather than the exception. Co-occurrence is generally assumed to be a consequence of risk factors that are shared between disorders, for example, working memory. However, it should not be assumed that all dyslexics have problems with mathematics, although the percentage may be very high, or that all dyscalculics have problems with reading and writing. Because mathematics is very developmental, any insecurity or uncertainty in early topics will impact on later topics, hence to need to take intervention back to basics. However, it may be worked out in order to decrease its degree of severity. For example, disMAT, an app developed for android may help children to apply mathematical concepts, without much effort, that is turning in itself, a promising tool to dyscalculia treatment. Thus, this work will focus on the development of a Decision Support System to estimate children evidences of dyscalculia, based on data obtained on-the-fly with disMAT. The computational framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, grounded on a Case-based approach to computing, that allows for the handling of incomplete, unknown, or even self-contradictory information.

Mapping the likelihood of foot-and-mouth disease introduction along the border between Brazil and Paraguay.

The objective of this work was to apply fuzzy majority multicriteria group decision?making to determine risk areas for foot?and?mouth disease (FMD) introduction along the border between Brazil and Paraguay. The study was conducted in three municipalities in the state of Mato Grosso do Sul, Brazil, located along the border with Paraguay. Four scenarios were built, applying the following linguistic quantifiers to describe risk factors: few, half, many, and most. The three criteria considered to be most likely to affect the vulnerability to introduction of FMD, according to experts? opinions, were: the introduction of animals in the farm, the distance from the border, and the type of property settlements. The resulting maps show a strong spatial heterogeneity in the risk of FMD introduction. The used methodology brings out a new approach that can be helpful to policy makers in the combat and eradication of FMD.

Bank Governance and the Bail-in in the EU. A Law & Finance analysis on the role of bail-inable creditors

This dissertation assesses the impact of the EU Directive on Bank Recovery and Resolution (BRRD) on bank corporate governance and investigates a fundamental question. Can the resolution framework for distressed banks enhance the quality of banks’ decision making? According to the Directive, the Resolution Authority can impose losses on bank’s creditors in case of distress through a bail-in. Bail-inable creditors become residual claimants of the bank, contingent on its distress. The first part of the dissertation establishes an analytical framework for bank governance, starting from the problem of what can be defined as “good governance” in banking. The dissertation hypothesizes that governance regulation represents a necessary link between the incentives of corporate constituencies and the goals of substantive regulation. The second part builds upon this analytical framework and carries out a positive analysis encompassing three channels of debt governance; namely, price internalisation of risk; contractual arrangements and the discrete impact of different type of creditors. The existence of a resolution framework should incentivise bail-inable creditors to better discipline the borrowing bank; yet, the design of both the capital and resolution regulation largely foreclose such possibility to creditors. Against this backdrop, the third part of the dissertation moves to normative considerations. The approach to this normative part combines and complements the study of cash flow rights of the management with the study of the voting rights to bail-inable creditors. On the cash flow side, the dissertation proposes to include bail-inable debt as part of the variable remuneration for bank risk-takers. On the voting right, the proposal is to grant a limited basket of ex-ante governance rights to bail-inable creditors. Such a unified approach is rather uncommon in the literature, where cash flow rights and voting rights are often approached separately whereas those complement each other in the dissertation.