The field of strategic management addresses challenges that firms encounter in an attempt to remain competitive. The ability to explain variation in firm success through examination of knowledge flows has become a prominent focus of research in the strategic management literature. Specifically, researchers have sought to further examine how firms convert knowledge, a phenomenon conceptualized as absorptive capacity. Absorptive capacity is the firm’s ability to acquire, assimilate, transform, and exploit knowledge. Few studies have captured the richness and multi-dimensionality of absorptive capacity, and it remains to be understood how the dimensions of the phenomenon convert knowledge. Furthermore, how absorptive capacity influences the firm remains to be understood. To address these research gaps, this dissertation seeks to (1) determine how absorptive capacity converts knowledge, and (2) determine how absorptive capacity influences firm capabilities. The research questions are investigated using structural modeling techniques to analyze data collected from software-industry firms. The findings offer contributions to the absorptive capacity and capability literatures. For example, absorptive capacity is hypothesized to consist of complex relationships among its internal dimensions. However, findings of this study suggest the relationships among the dimensions are linear in nature. This finding is in line with the theoretical foundations of and early literature on absorptive capacity but contrary to recent conceptualizations, which suggests relationships among the dimensions are more closely related to the theoretical origins of absorptive capacity. Additionally, to examine how absorptive capacity influences the firm, a capability-based perspective is used to hypothesize the influence of absorptive capacity on firm capabilities. Findings suggest absorptive capacity positively influences each dimension of firm capabilities (e.g., operational, customer, and innovation capabilities); thus, absorptive capacity influences the firm by altering firm capabilities. Given the richness of the findings, numerous fields are likely to benefit from this investigation. Through an examination of absorptive capacity and capabilities, this study contributes to the understanding of the absorptive capacity phenomenon and offers insight into how the phenomenon influences the firm. Furthermore, practical implications are offered for managers interested in enhancing firm competitiveness.

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Small and medium-sized enterprises (SMEs) in Peru present problems such as access to the national market due to limited capital or access to technology compared to large companies. However, they also lack an adequate definition and conceptualization of their processes, as well as a low level of business information transfer, which causes an absence in the measurement, control of processes and low operational performance. Given this situation, we propose the application and implementation of knowledge management tools in a company dedicated to the marketing and distribution of school supplies, which represents an SME in Peru. The tools used as the map of processes and flowcharts of the different processes were used to make the participants of the processes known. Through the realization of training, performance evaluations and internal audit, the learning of the operator is analyzed. As a result, there was a 57.63% decrease in errors in armed orders during picking, as well as a decrease of 7.98% and 8.59% of times in the execution of the processes under study for small orders and larger orders, respectively. Similarly, 96.56% of dispatches generated correctly were obtained.

We are living in an unjust world where the majority of humanity is subject to unequal economic and public policy systems that perpetuate cycles of poverty. Civil society, of which international NGOs are major players, are acknowledging the need for systemic, transformational change, which has to include meaningful participation in decision making processes by those whom are most vulnerable. In order to more effectively play this role, a number of international NGOs are moving decentralised structures (often comprised of independent entities at country level) to legitimately represent their primary constituents - those that are vulnerable, living in poverty, mostly in the global South. A consequence of this trajectory is added internal complexity and the creation of new management challenges, as decision making processes become more participatory and transparent. In addition, this new reality of complex federal structures also requires that power inequities between entities, are openly acknowledged and managed. Despite these challenges, this is a non-negotiable journey for many international NGOs and they acknowledge the need to adapt their management mechanisms to better handle this internal complexity. First-hand experience sparked the interest to apply operational research and system dynamics approaches to one such management mechanism, that of resource planning and allocation within international NGOs. This study aims to develop a set of insights, based on the system dynamics model, that could be useful to international NGO decision makers as they respond to their “real life” resource allocation challenges. Problem structuring methods are applied to these resource allocation challenges to gain a deeper understanding of the core components of resource allocation in order to develop a generic system dynamics model that simulates the necessary behaviours based on stakeholder input. A set of management scenarios are developed and form the basis for conducting experimental runs on the generic system dynamics model, testing different parameters in an effort to compare quantitative results. These quantitative results are used to compare performance against the original generic model, analysing trends and model behaviour to inform qualitative recommendations and conclusions.

Dans cette thèse, nous nous intéressons à l’optimisation robuste. Plus précisément,nous nous intéresserons aux problèmes linéaires mixtes bi-niveaux, c’est à dire aux problèmes dans lesquels le processus de décision est divisé en deux parties : dans un premier temps, les valeurs optimales des variables dites "de décisions" seront calculées ; puis, une fois que l’incertitude sur les données est levée, nous calculerons les valeurs des variables dites "de recours". Dans cette thèse, nousnous limiterons au cas où les variables de deuxième étape, dites "de recours", sontcontinues.Dans la première partie de cette thèse, nous nous concentrerons sur l’étudethéorique de tels problèmes. Nous commencerons par résoudre un problème linéairesimplifié dans lequel l’incertitude porte seulement sur le membre droit descontraintes, et est modélisée par un polytope bien particulier. Nous supposerons enoutre que le problème vérifie une propriété dite "de recours complet", qui assureque, quelles que soient les valeurs prises par les variables de dcisions, si ces dernières sont admissibles, alors le problème admet toujours une solution réalisable, et ce, quelles que soient les valeurs prises par les paramètres incertains. Nous verrons alors une méthode permettant, à partir d’un programme robuste quelconque, de se ramener à un programme robuste équivalent dont le problème déterministe associévérifie la propriété de recours complet. Avant de traiter le cas général, nous nouslimiterons d’abord au cas o les variables de décisions sont entières. Nous testeronsalors notre approche sur un problème de production. Ensuite, après avoir remarquéque l’approche développée dans les chapitres précédents ne se généralisait pasnaturellement aux polytopes qui n’ont pas des points extrmes 0-1, nous montreronscomment, en utilisant des propriétés de convexité du problème, résoudre le problème robuste dans le cas général. Nous en déduirons alors des résultats de complexité sur le problème de deuxième étape, et sur le problème robuste. Dans la suite de cette partie nous tenterons d’utiliser au mieux les informations probabilistes que l’on a sur les données aléatoires pour estimer la pertinence de notre ensemble d’incertitude.Dans la deuxième partie de cette thèse, nous étudierons un problème de conceptionde parc hybride de production d’électricité. Plus précisément, nous chercheronsà optimiser un parc de production électrique constitué d’éoliennes, de panneauxsolaires, de batteries et d’un générateur à diesel, destiné à répondre à unedemande locale d’énergie électrique. Il s’agit de déterminer le nombre d’éoliennes,de panneaux solaires et de batteries à installer afin de répondre à la demande pourun cot minimum. Cependant, les données du problème sont très aléatoires. En effet,l’énergie produite par une éolienne dépend de la force et de la direction du vent ; celle produite par un panneau solaire, de l’ensoleillement et la demande en électricité peut tre liée à la température ou à d’autres paramètres extérieurs. Pour résoudre ce problème, nous commencerons par modéliser le problème déterministeen un programme linéaire mixte. Puis nous appliquerons directement l’approche de la première partie pour résoudre le problème robuste associé. Nous montrerons ensuite que le problème de deuxième étape associé, peut se résoudre en temps polynomial en utilisant un algorithme de programmation dynamique. Enfin, nous donnerons quelques généralisations et améliorations pour notre problème. / Robust optimization is a recent approach to study problems with uncertain datathat does not rely on a prerequisite precise probability model but on mild assumptionson the uncertainties involved in the problem.We studied a linear two-stage robustproblem with mixed-integer first-stage variables and continuous second stagevariables. We considered column wise uncertainty and focused on the case whenthe problem doesn’t satisfy a "full recourse property" which cannot be always satisfied for real problems. We also studied the complexity of the robust problemwhich is NP-hard and proved that it is actually polynomial solvable when a parameterof the problem is fixed.We then applied this approach to study a stand-alonehybrid system composed of wind turbines, solar photovoltaic panels and batteries.The aim was to determine the optimal number of photovoltaic panels, wind turbinesand batteries in order to serve a given demand while minimizing the total cost of investment and use. We also studied some properties of the second stage problem, in particular that the second stage problem can be solvable in polynomial time using dynamic programming.

A predicted association between family relations and cognitive development and the emergence of adolescent egocentrism was explored in this study. A sample of seventh grade boys (n=131) and girls (n=120) completed Elkind and Bowen's Imaginary Audience Scale (a measure of egocentrism) and selected items from Heilbrun's Parent-Child Interaction Rating Scale and Schaefer's Parent-Behavior Inventory. A modified version of Lawson's Classroom Test of Formal Operations was used to measure cognitive development. Contrary to a theoretical based hypothesis a negative rather than positive relationship was found between level of formal operational thought egocentrism. For parenting style, perceived rejection/control and emotional support was associated with diminished egocentrism. Mixed results were found for perceived physical effect and egocentrism. Perceived parental withdrawal heightened egocentrism for both sexes. The data provide an alternative model to past cognitive development theory for the development of egocentrism. Parental socialization factors were found to contribute as much variance to the level of egocentrism as did level of formal operational thought.

The implementation of a fast track section is a commonly used strategy to improve patient flow in emergency departments (EDs). A fast track section reserves resources (beds, doctors and nurses) for lower acuity patients, and is thus aimed to reduce the wait time and length of stay of these patients. We use a discrete event simulation to investigate the impact of adding a fast track section to an emergency department. We quantify the effect of introducing a fast track on length of stay and waiting time to bed for low and high acuity patients in a crowded ED and compare it to an ED without fast track (Combined ED). We simulate a crowded ED by increasing the patient arrival rate, changing the acuity mix and increasing the time taken for admitted patients in the ED to obtain an inpatient bed (boarding time). We demonstrate that, when compared to a Combined ED with the same number of resources, the introduction of a fast track reduces the wait time to bed for lower acuity patients. However, this comes at the cost of increased waiting time for some higher acuity patients, which is unacceptable in practice. In investigating the solutions to this problem, we find that changing patient prioritization is the most effective way of reducing wait times under crowding. This change in priority does not require the addition of beds, doctors and nurses, and is therefore a cost-effective approach. Finally, we discuss the implications of our results for emergency departments.

Java is currently a widely used programming language. However, there is no formal definition of Java's semantics. Consequently, Java code does not have a universal meaning. This work discusses recent attempts to formalize Java and presents a new formalism of Java called Javalite. In contrast to common approaches to formalization, Javalite is purely syntactic in its definition. Syntactic operational semantics use the structure of the language to define its behavior. Javalite models most Java features with notable exceptions being threads, reflection, and interfaces. This work presents an executable semi-formal model of Javalite in PLT Redex. Being executable means that Javalite programs can be run using this model. We then render the semi-formal model in the Coq theorem prover and present theorems stating that the operational semantics are decidable and deterministic. This formal model can then be used to facilitate research in areas such as proving properties of algorithms that perform various analyses on Java code, e.g. verification, optimization, and refactoring.

An Optimization Approach to Employee Scheduling Using Fuzzy Logic William G. Spence Selection of sales employees is critical because the sales employees represent the company’s image, competitive advantage, technology, and values. In many service systems the majority of consumer contact is with the sales department. Since there are different types of customers, scheduling quality salespersons who can adequately help consumers may affect revenue. This thesis proposes a new methodology for the scheduling of employees in a service system. The methodology uses Fuzzy Logic to calculate possible sales and Linear Programming to create an optimal schedule. This approach enables the rating of sales employees with respect to three customer’s types (Lookie Lou, Price Shopper and Buyer). The salesperson rating, along with customer arrival distribution is then used to optimize sale person scheduling, with the objective of revenue maximization. The uniqueness of this thesis lies in the combination of Fuzzy Logic and Linear Programming. The combination of these two disciplines provides an adaptive tool that can be used to optimize employee scheduling based on personality traits.

Mergers are the combining of two or more firms to create synergies. These synergies may come from various sources such as operational synergies come from economies of scale or financial synergies come from increased value of securities of the firm. There are vast amount of studies analysing operational synergies of mergers. This study analyses the financial ones. This way the dynamics of purely financial synergies can be revealed. Purely financial synergies can be transformed into financial instruments such as securitization. While analysing financial synergies the puzzle of distribution of financial synergies between claimholders is investigated. Previous literature on mergers showed that bondholders may gain more than existing shareholders of the merging firms. This may become rather controversial. A merger may be synergistic but it does not necessarily mean that shareholders¿ wealth will increase. Managers and/or shareholders are the parties making the merger decision. If managers are acting to the best interest of shareholders then they would try to increase shareholders¿ wealth. To solve this problem first the dynamics of mergers were analysed and then new strategies developed and demonstrated to transfer the financial synergies to the shareholders.