17 resultados para Uncertainty management


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En un mundo donde el cambio es constante y cada vez más vertiginoso, la innovación es el combustible que utilizan las empresas que permite su renovación constante y, como consecuencia, su supervivencia en el largo plazo. La innovación es sin dudas un elemento fundamental para determinar la capacidad de las empresas en crear valor a lo largo del tiempo, y por ello, las empresas suelen dedicar esfuerzos considerables y recursos de todo tipo para identificar nuevas alternativas de innovación que se adapten a su estrategia, cultura, objetivos y ambiciones corporativas. Una forma específica para llevar a cabo la innovación es la innovación abierta. Esta se entiende como la innovación que se realiza de manera conjunta con otras empresas o participantes del ecosistema. Cabe la aclaración que en este documento se toma la definición de ecosistema referida al conjunto de clientes, proveedores, competidores y otros participantes que interactúan en un mismo entorno donde existen posiciones de liderazgo que pueden cambiar a lo largo del tiempo (Moore 1996). El termino de innovación abierta fue acuñado por Henry Chesbrough hace algo mas de una década para referirse a esta forma particular de organizar la innovación corporativa. Como se observa en el presente trabajo la innovación abierta es un nuevo paradigma que ha capturado el interés académico y empresarial desde algo más de una década. Se verán varios casos de innovación abierta que se están llevando a cabo en diversos países y sectores de la economía. El objetivo principal de este trabajo de investigación es el de desarrollar y explicar un modelo de relación entre la innovación abierta y la creación de valor en las empresas. Para ello, y como objetivos secundarios, se ha investigado los elementos de un Programa de Innovación Abierta, los impulsores 1 de creación de valor, el proceso de creación de valor y, finalmente, la interacción entre estos tres elementos. Como producto final de la investigación se ha desarrollado un marco teórico general para establecer la conexión entre la innovación abierta y la creación de valor que facilita la explicación de la interacción entre ambos elementos. Se observa a partir de los casos de estudio que la innovación abierta puede abarcar todos los sectores de la economía, múltiples geografías y empresas de distintos tamaños (grandes empresas, pequeñas y medianas empresas, incluso empresas de reciente creación) cada una de ellas con distinta relevancia dentro del ecosistema en el que participan. Elementos de un Programa de Innovación Abierta La presente investigación comienza con la enumeración de los distintos elementos que se encuentran presentes en los Programas de Innovación Abierta. De esta manera, se describen los diversos elementos que se han identificado a través de la revisión de la literatura académica que se ha llevado a cabo. En función de una serie de características comunes, los distintos elementos se agrupan en cuatro niveles diferentes para lograr un mejor entendimiento de los Programas de Innovación Abierta. A continuación se detallan estos elementos § Organización del Programa. En primer lugar se menciona la existencia de una estructura organizativa capaz de cumplir una serie de objetivos establecidos previamente. Por su naturaleza de innovación abierta deberá existir cierto grado de interacción entre los distintos miembros que participen en el proceso de innovación. § Talento Interno. El talento interno asociado a los programas de innovación abierta juega un rol fundamental en la ejecución y éxito del programa. Bajo este nivel se asocian elementos como la cultura de innovación abierta y el liderazgo como mecanismo para entender uno de los elementos que explica el grado de adopción de innovación en una empresa. Estrechamente ligados al liderazgo se encuentran los comportamientos organizacionales como elementos diferenciadores para aumentar las posibilidades de creación de innovación abierta. § Infraestructura. En este nivel se agrupan los elementos relacionados con la infraestructura tecnológica necesaria para llevar a cabo el programa incluyendo los procesos productivos y las herramientas necesarias para la gestión cotidiana. § Instrumentos. Por último, se mencionan los instrumentos o vehículos que se utilizan en el entorno corporativo para implementar innovación abierta. Hay varios instrumentos disponibles como las incubadoras corporativas, los acuerdos de licenciamiento o las áreas de capital de riesgo corporativo. Para este último caso se hará una mención especial por el creciente y renovado interés que ha despertado tanto en el entorno académico como empresarial. Se ha identificado al capital de riesgo corporativo como un de los elementos diferenciales en el desarrollo de la estrategia de innovación abierta de las empresas ya que suele aportar credibilidad, capacidad y soporte tecnológico. Estos cuatro elementos, interactuando de manera conjunta y coordinada, tienen la capacidad de crear, potenciar e incluso desarrollar impulsores de creación de valor que impactan en la estrategia y organización de la empresa y partir de aquí en su desempeño financiero a lo largo del tiempo. Los Impulsores de Creación de Valor Luego de identificar, ordenar y describir los distintos elementos presentes en un Programa de Innovación Abierta se ha avanzado en la investigación con los impulsores de creación de valor. Estos pueden definirse como elementos que potencian o determinan la capacidad de crear valor dentro del entorno empresarial. Como se puede observar, se detallan estos impulsores como punto de interacción entre los elementos del programa y el proceso de creación de valor corporativo. A lo largo de la presente investigación se han identificado 6 impulsores de creación de valor presentes en un Programa de Innovación Abierta. § Nuevos Productos y Servicios. El impulsor de creación de valor más directo y evidente en un Programa de Innovación Abierta es la capacidad de crear nuevos productos y servicios dado que se relacionan directamente con el proceso de innovación de la empresa § Acceso a Mercados Adyacentes. El proceso de innovación también puede ser una fuente de valor al permitir que la empresa acceda a mercados cercanos a su negocio tradicional, es decir satisfaciendo nuevas necesidades de sus clientes existentes o de nuevos clientes en otro mercado. § Disponibilidad de Tecnologías. La disponibilidad de tecnologías es un impulsor en si mismo de la creación de valor. Estas pueden ser tanto complementarias como de apalancamiento de tecnologías ya existentes dentro de la empresa y que tengan la función de transformar parte de los componentes de la estrategia de la empresa. § Atracción del Talento Externo. La introducción de un Programa de Innovación Abierta en una empresa ofrece la oportunidad de interactuar con otras organizaciones del ecosistema y, por tanto, de atraer el talento externo. La movilidad del talento es una característica singular de la innovación abierta. § Participación en un Ecosistema Virtuoso. Se ha observado que las acciones realizadas en el entorno por cualquiera de los participantes también tendrán un claro impacto en la creación de valor para el resto de participantes por lo tanto la participación en un ecosistema virtuoso es un impulsor de creación de valor presente en la innovación abierta. § Tecnología “Dentro--‐Fuera”. Como último impulsor de valor es necesario comentar que la dirección que puede seguir la tecnología puede ser desde la empresa hacia el resto del ecosistema generando valor a partir de disponibilizar tecnologías que no son de utilidad interna para la empresa. Estos seis impulsores de creación de valor, presentes en los procesos de innovación corporativos, tienen la capacidad de influir en la estrategia y organización de la empresa aumentando su habilidad de crear valor. El Proceso de Creación de Valor en las Empresas Luego se ha investigado la práctica de la gestión basada en valor que sostiene la necesidad de alinear la estrategia corporativa y el diseño de la organización con el fin de obtener retornos financieros superiores al resto de los competidores de manera sostenida, y finalmente crear valor a lo largo del tiempo. Se describe como los impulsores de creación de valor influyen en la creación y fortalecimiento de las ventajas competitivas de la empresa impactando y alineando su estrategia y organización. Durante la investigación se ha identificado que las opciones reales pueden utilizarse como una herramienta para gestionar entornos de innovación abierta que, por definición, tienen altos niveles de incertidumbre. Las opciones reales aportan una capacidad para la toma de decisiones de forma modular y flexible que pueden aplicarse al entorno corporativo. Las opciones reales han sido particularmente diseñadas para entender, estructurar y gestionar entornos de múltiples incertidumbres y por ello tienen una amplia aplicación en los entornos de innovación. Se analizan los usos potenciales de las opciones reales como complemento a los distintos instrumentos identificados en los Programas de Innovación Abierta. La Interacción Entre los Programas de Innovación Abierta, los Impulsores de Creación de Valor y el Proceso de Creación de Valor A modo de conclusión del presente trabajo se puede mencionar que se ha desarrollado un marco general de creación de valor en el entorno de los Programas de Innovación Abierta. Este marco general incluye tres elementos fundamentales. En primer lugar describe los elementos que se encuentran presentes en los Programas de Innovación Abierta, en segundo lugar como estos programas colaboran en la creación de los seis impulsores de creación de valor que se han identificado y finalmente en tercer lugar como estos impulsores impactan sobre la estrategia y la organización de la empresa para dar lugar a la creación de valor de forma sostenida. A través de un Programa de Innovación Abierta, se pueden desarrollar los impulsores de valor para fortalecer la posición estratégica de la empresa y su capacidad de crear de valor. Es lo que denominamos el marco de referencia para la creación de valor en un Programa de Innovación Abierta. Se presentará la idea que los impulsores de creación de valor pueden colaborar en generar una estrategia óptima que permita alcanzar un desempeño financiero superior y lograr creación de valor de la empresa. En resumen, se ha desarrollado un modelo de relación que describe el proceso de creación de valor en la empresa a partir de los Programas de Innovación Abierta. Para ello, se han identificado los impulsores de creación de valor y se ha descripto la interacción entre los distintos elementos del modelo. ABSTRACT In a world of constant, accelerating change innovation is fuel for business. Year after year, innovation allows firms to renew and, therefore, advance their long--‐term survival. Undoubtedly, innovation is a key element for the firms’ ability to create value over time. Companies often devote considerable effort and diverse resources to identify innovation alternatives that could fit into their strategy, culture, corporate goals and ambitions. Open innovation refers to a specific approach to innovate by collaborating with other firms operating within the same business ecosystem.2 The term open innovation was pioneered by Henry Chesbrough more than a decade ago to refer to this particular mode of driving corporate innovation. Open innovation is a new paradigm that has attracted academic and business interest for over a decade. Several cases of open innovation from different countries and from different economic sectors are included and reviewed in this document. The main objective of this study is to explain and develop a relationship model between open innovation and value creation. To this end, and as secondary objectives, we have explored the elements of an Open Innovation Program, the drivers of value creation, the process of value creation and, finally, the interaction between these three elements. As a final product of the research we have developed a general theoretical framework for establishing the connection between open innovation and value creation that facilitates the explanation of the interaction between the two. From the case studies we see that open innovation can encompass all sectors of the economy, multiple geographies and varying businesses – large companies, SMEs, including (even) start--‐ups – each with a different relevance within the ecosystem in which they participate. Elements of an Open Innovation Program We begin by listing and describing below the items that can be found in an Open Innovation Program. Many of such items have been identified through the review of relevant academic literature. Furthermore, in order to achieve a better understanding of Open Innovation, we have classified those aspects into four different categories according to the features they share. § Program Organization. An organizational structure must exist with a degree of interaction between the different members involved in the innovation process. This structure must be able to meet a number of previously established objectives. § Internal Talent. Internal talent plays a key role in the implementation and success of any Open Innovation program. An open innovation culture and leadership skills are essential for adopting either radical or incremental innovation. In fact, leadership is closely linked to organizational behavior and it is essential to promote open innovation. § Infrastructure. This category groups the elements related to the technological infrastructure required to carry out the program, including production processes and daily management tools. § Instruments. Finally, we list the instruments or vehicles used in the corporate environment to implement open innovation. Several instruments are available, such as corporate incubators, licensing agreements or venture capital. There has been a growing and renewed interest in the latter, both in academia and business circles. The use of corporate venture capital to sustain the development of the open innovation strategy brings ability, credibility, and technological support to the process. The combination of elements from these four categories, interacting in a coordinated way, makes it possible to create, enhance and develop value creation drivers that may impact the company’s strategy and organization and affect its financial performance over time. The Drivers of Value Creation After identifying describing and categorizing the different elements present in an Open Innovation Program our research examines the drivers of value creation. These can be defined as elements that enhance or determine the ability to create value in the business environment. As can be seen, these drivers can act as interacting points between the elements of the program and the process of value creation. The study identifies six drivers of value creation that might be found in an Open Innovation Program. § New Products and Services. The more direct and obvious driver of value creation in any Open Innovation Program is the ability to create new products and services. This is directly related to the company’s innovation process. § Access to Adjacent Markets. The innovation process can also serve as a source of value by granting access to adjacent markets through satisfying new needs for existing customers or attracting new customers from other markets. § Availability of Technologies. The availability of technology is in itself a driver for value creation. New technologies can either be complementary and/or can leverage existing technologies within the firm. They can partly transform certain elements of the company’s strategy. § External Talent Strategy. Incorporating an Open Innovation Program offers the opportunity to interact with other organizations operating in the same ecosystem and can therefore attract external skilled resources. Talent mobility is a unique feature of open innovation. § Becoming Part of a Virtuous Circle. The actions carried out in the environment by any of its members will also have a clear impact on value creation for the other participants. Participation in a virtuous ecosystem is thus a driver for value creation in an open innovation strategy. § Inside--‐out Technology. Value creation may also evolve by allowing other firms in the ecosystem to incorporate internally developed under--‐utilized technologies into their own innovation processes. These six drivers that are present in the innovation process can influence the strategy and the organization of the company, increasing its ability to create value. The Value Creation Process Value--‐based management is the management approach that requires aligning the corporate strategy and the organizational design to create value and obtain sustained financial returns (at least, higher returns than its competitors). We describe how the drivers of value creation can enhance corporate advantages by aligning its strategy and organization. During this study, we were able to determine that real options can be used as managing tools in open innovation environments which, by definition, have high uncertainty levels. Real options provide capability for flexible and modular decision--‐making in the business environment. In particular, real options have been designed for uncertainty management and, therefore, they may be widely applied in innovation environments. We analyze potential uses of real options to supplement the various instruments identified in the Open Innovation programs. The Interaction Between Open Innovation Programs, Value Creation drivers and Value Creation Process As a result of this study, we have developed a general framework for value creation in Open Innovation Programs. This framework includes three key elements. We first described the elements that are present in Open Innovation Programs. Next, we showed how these programs can boost six drivers of value creation that have been identified. Finally, we analyzed how the drivers impact on the strategy and organization of the company in order to lead to the creation of sustainable value. Through an Open Innovation Program, value drivers can be developed to strengthen a company’s strategic position and its ability to create value. That is what we call the framework for value creation in the Open Innovation Program. Value drivers can collaborate in generating an optimal strategy that helps foster a superior financial performance and a sustained value creation process. In sum, we have developed a relationship model that describes the process of creating value in a firm with an Open Innovation Program. We have identified the drivers of value creation and described how the different elements of the model interact with each other.

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In the last few years, technical debt has been used as a useful means for making the intrinsic cost of the internal software quality weaknesses visible. This visibility is made possible by quantifying this cost. Specifically, technical debt is expressed in terms of two main concepts: principal and interest. The principal is the cost of eliminating or reducing the impact of a, so called, technical debt item in a software system; whereas the interest is the recurring cost, over a time period, of not eliminating a technical debt item. Previous works about technical debt are mainly focused on estimating principal and interest, and on performing a cost-benefit analysis. This cost-benefit analysis allows one to determine if to remove technical debt is profitable and to prioritize which items incurring in technical debt should be fixed first. Nevertheless, for these previous works technical debt is flat along the time. However the introduction of new factors to estimate technical debt may produce non flat models that allow us to produce more accurate predictions. These factors should be used to estimate principal and interest, and to perform cost-benefit analysis related to technical debt. In this paper, we take a step forward introducing the uncertainty about the interest, and the time frame factors so that it becomes possible to depict a number of possible future scenarios. Estimations obtained without considering the possible evolution of the interest over time may be less accurate as they consider simplistic scenarios without changes.

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Following the Integrated Water Resources Management approach, the European Water Framework Directive demands Member States to develop water management plans at the catchment level. Those plans have to integrate the different interests and must be developed with stakeholder participation. To face these requirements, managers need tools to assess the impacts of possible management alternatives on natural and socio-economic systems. These tools should ideally be able to address the complexity and uncertainties of the water system, while serving as a platform for stakeholder participation. The objective of our research was to develop a participatory integrated assessment model, based on the combination of a crop model, an economic model and a participatory Bayesian network, with an application in the middle Guadiana sub-basin, in Spain. The methodology is intended to capture the complexity of water management problems, incorporating the relevant sectors, as well as the relevant scales involved in water management decision making. The integrated model has allowed us testing different management, market and climate change scenarios and assessing the impacts of such scenarios on the natural system (crops), on the socio-economic system (farms) and on the environment (water resources). Finally, this integrated assessment modelling process has allowed stakeholder participation, complying with the main requirements of current European water laws.

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A participatory modelling process has been conducted in two areas of the Guadiana river (the upper and the middle sub-basins), in Spain, with the aim of providing support for decision making in the water management field. The area has a semi-arid climate where irrigated agriculture plays a key role in the economic development of the region and accounts for around 90% of water use. Following the guidelines of the European Water Framework Directive, we promote stakeholder involvement in water management with the aim to achieve an improved understanding of the water system and to encourage the exchange of knowledge and views between stakeholders in order to help building a shared vision of the system. At the same time, the resulting models, which integrate the different sectors and views, provide some insight of the impacts that different management options and possible future scenarios could have. The methodology is based on a Bayesian network combined with an economic model and, in the middle Guadiana sub-basin, with a crop model. The resulting integrated modelling framework is used to simulate possible water policy, market and climate scenarios to find out the impacts of those scenarios on farm income and on the environment. At the end of the modelling process, an evaluation questionnaire was filled by participants in both sub-basins. Results show that this type of processes are found very helpful by stakeholders to improve the system understanding, to understand each others views and to reduce conflict when it exists. In addition, they found the model an extremely useful tool to support management. The graphical interface, the quantitative output and the explicit representation of uncertainty helped stakeholders to better understand the implications of the scenario tested. Finally, the combination of different types of models was also found very useful, as it allowed exploring in detail specific aspects of the water management problems.

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The operating theatres are the engine of the hospitals; proper management of the operating rooms and its staff represents a great challenge for managers and its results impact directly in the budget of the hospital. This work presents a MILP model for the efficient schedule of multiple surgeries in Operating Rooms (ORs) during a working day. This model considers multiple surgeons and ORs and different types of surgeries. Stochastic strategies are also implemented for taking into account the uncertain in surgery durations (pre-incision, incision, post-incision times). In addition, a heuristic-based methods and a MILP decomposition approach is proposed for solving large-scale ORs scheduling problems in computational efficient way. All these computer-aided strategies has been implemented in AIMMS, as an advanced modeling and optimization software, developing a user friendly solution tool for the operating room management under uncertainty.

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The author participated in the 6 th EU Framework Project ―Q-pork Chains (FP6-036245-2)‖ from 2007 to 2009. With understanding of work reports from China and other countries, it is found that compared with other countries, China has great problems in pork quality and safety. By comparing the pork chain management between China and Spain, It is found that the difference in governance structure is one of the main differences in pork chain management between Spain and China. In China, spot-market relationship still dominates governance structure of pork chain, especially between the numerous house-hold pig holders and the great number of small slaughters. While in Spain, chain agents commonly apply cooperatives or integrations to cooperate. It also has been proven by recent studies, that in quality management at the chain level that supply chain integration has a direct effect on quality management practices (Han, 2010). Therefore, the author started to investigate the governance structure choices in supply chain management. And it has been set as the first research objective, which is to explain the governance structure choices process and the influencing factors in supply chain management, analyzing the pork chains cases in Spain and in China. During the further investigation, the author noticed the international trade of pork between Spain and China is not smooth since the signature of bi-lateral agreement on pork trade in 2007. Thus, another objective of the research is to find and solve the problems exist in the international pork chain between Spain and China. For the first objective, to explain the governance structure choices in supply chain management, the thesis conducts research in three main sections. 10 First of all, the thesis gives a literature overview in chapter two on Supply Chain Management (SCM), agri-food chain management and pork chain management. It concludes that SCM is a systems approach to view the supply chains as a whole, and to manage the total flow of goods inventory from the supplier to the ultimate customer. It includes the bi-directional flow of products (materials and services) and information, and the associated managerial and operational activities. And it also is a customer focus to create unique and individual source of customer value with an appropriate use of resources, leading to customer satisfaction and building competitive chain advantages. Agri-food chain management and pork chain management are applications of SCM in agri-food sector and pork sector respectively. Then, the research gives a comparative study in chapter three in the pork chain and pork chain management between Spain and China. Many differences are found, while the main difference is governance structure in pork chain management. Furthermore, the author gives an empirical study on governance structure choice in chapter five. It is concluded that governance structure of supply chain consists of a collection of rules/institutions/constraints structuring the transactions between the various stakeholders. Based on the overview on literatures closely related with governance structure, such as transaction cost economics, transaction value analysis and resource-based view theories, seven hypotheses are proposed, which are: Hypothesis 1: Transaction cost has positive relationship with governance structure choice Hypothesis 2: Uncertainty has positive relationship with transaction cost; higher uncertainty exerts high transaction cost Hypothesis 3: The relationship between asset specificity and transaction cost is positive Hypothesis 4: Collaboration advantages and governance structure choice have positive relationship11 Hypothesis 5: Willingness to collaborate has positive relationship with collaboration advantages Hypothesis 6: Capability to collaborate has positive relationship with collaboration advantages Hypothesis 7: Uncertainty has negative effect on collaboration advantages It is noted that as transaction cost value is negative, the transaction cost mentioned in the hypotheses is its absolute value. To test the seven hypotheses, Structural Equation Model (SEM) is applied and data collected from 350 pork slaughtering and processing companies in Jiangsu, Shandong and Henan Provinces in China is used. Based on the empirical SEM model and its results, the seven hypotheses are proved. The author generates several conclusions accordingly. It is found that the governance structure choice of the chain not only depends on transaction cost, it also depends on collaboration advantages. Exchange partners establish more stable and more intense relationship to reduce transaction cost and to maximize collaboration advantages. ―Collaboration advantages‖ in this thesis is defined as the joint value achieved through transaction (mutual activities) of agents in supply chains. This value forms as improvements, mainly in mutual logistics systems, cash response, information exchange, technological improvements and innovative improvements and quality management improvements, etc. Governance structure choice is jointly decided by transaction cost and collaboration advantages. Chain agents take different governance structures to coordinate in order to decrease their transaction cost and to increase their collaboration advantages. In China´s pork chain case, spot market relationship dominates the governance structure among the numerous backyard pig farmer and small family slaughterhouse 12 as they are connected by acquaintance relationship and the transaction cost in turn is low. Their relationship is reliable as they know each other in the neighborhood; as a result, spot market relationship is suitable for their exchange. However, the transaction between large-scale slaughtering and processing industries and small-scale pig producers is becoming difficult. The information hold back behavior and hold-up behavior of small-scale pig producers increase transaction cost between them and large-scale slaughtering and processing industries. Thus, through the more intense and stable relationship between processing industries and pig producers, processing industries reduce the transaction cost and improve the collaboration advantages with their chain partners, in which quality and safety collaboration advantages be increased, meaning that processing industries are able to provide consumers products with better quality and higher safety. It is also drawn that transaction cost is influenced mainly by uncertainty and asset specificity, which is in line with new institutional economics theories developed by Williamson O. E. In China´s pork chain case, behavioral uncertainty is created by the hold-up behaviors of great numbers of small pig producers, while big slaughtering and processing industries having strong asset specificity. On the other hand, ―collaboration advantages‖ is influenced by chain agents´ willingness to collaborate and chain agents´ capabilities to cooperate. With the fast growth of big scale slaughtering and processing industries, they are more willing to know and make effort to cooperate with their chain members, and they are more capable to create joint value together with other chain agents. Therefore, they are now the main chain agents who drive more intense and stable governance structure in China‘s pork chain. For the other objective, to find and solve the problems in the international pork chain between Spain and China, the research gives an analysis in chapter four on the 13 international pork chain. This study gives explanations why the international trade of pork between Spain and China is not sufficient from the chain perspective. It is found that the first obstacle is the high quality and safety requirement set by Chinese government. It makes the Spanish companies difficult to get authorities to export. Other aspects, such as Spanish pork is not competitive in price compared with other countries such as Denmark, United States, Canada, etc., Chinese consumers do not have sufficient information on Spanish pork products, are also important reasons that Spain does not export great quantity of pork products to China. It is concluded that China´s government has too much concern on the quality and safety requirements to Spanish pork products, which makes trade difficult to complete. The two countries need to establish a more stable and intense trade relationship. They also should make the information exchange sufficient and efficient and try to break trade barriers. Spanish companies should consider proper price strategies to win the Chinese pork market

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Identifying, quantifying, and minimizing technical risks associated with investment decisions is a key challenge for mineral industry decision makers and investors. However, risk analysis in most bankable mine feasibility studies are based on the stochastic modelling of project “Net Present Value” (NPV)which, in most cases, fails to provide decision makers with a truly comprehensive analysis of risks associated with technical and management uncertainty and, as a result, are of little use for risk management and project optimization. This paper presents a value-chain risk management approach where project risk is evaluated for each step of the project lifecycle, from exploration to mine closure, and risk management is performed as a part of a stepwise value-added optimization process.

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The accurate prediction of the spent nuclear fuel content is essential for its safe and optimized transportation, storage and management. This isotopic evolution can be predicted using powerful codes and methodologies throughout irradiation as well as cooling time periods. However, in order to have a realistic confidence level in the prediction of spent fuel isotopic content, it is desirable to determine how uncertainties affect isotopic prediction calculations by quantifying their associated uncertainties.

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Improved management of nitrogen (N) in agriculture is necessary to achieve a sustainable balance between the production of food and other biomass, and the unwanted effects of N on water pollution, greenhouse gas emissions, biodiversity deterioration and human health. To analyse farm N-losses and the complex interactions within farming systems, efficient methods for identifying emissions hotspots and evaluating mitigation measures are therefore needed. The present paper aims to fill this gap at the farm and landscape scales. Six agricultural landscapes in Poland (PL), the Netherlands (NL), France (FR), Italy (IT), Scotland (UK) and Denmark (DK) were studied, and a common method was developed for undertaking farm inventories and the derivation of farm N balances, N surpluses and for evaluating uncertainty for the 222 farms and 11 440 ha of farmland included in the study. In all landscapes, a large variation in the farm N surplus was found, and thereby a large potential for reductions. The highest average N surpluses were found in the most livestock-intensive landscapes of IT, FR, and NL; on average 202 ± 28, 179 ± 63 and 178 ± 20 kg N ha−1 yr−1, respectively. All landscapes showed hotspots, especially from livestock farms, including a special UK case with large-scale landless poultry farming. Overall, the average N surplus from the land-based UK farms dominated by extensive sheep and cattle grazing was only 31 ± 10 kg N ha−1 yr−1, but was similar to the N surplus of PL and DK (122 ± 20 and 146 ± 55 kg N ha−1 yr−1, respectively) when landless poultry farming was included. We found farm N balances to be a useful indicator for N losses and the potential for improving N management. Significant correlations to N surplus were found, both with ammonia air concentrations and nitrate concentrations in soils and groundwater, measured during the period of N management data collection in the landscapes from 2007–2009. This indicates that farm N surpluses may be used as an independent dataset for validation of measured and modelled N emissions in agricultural landscapes. No significant correlation was found with N measured in surface waters, probably because of spatial and temporal variations in groundwater buffering and biogeochemical reactions affecting N flows from farm to surface waters. A case study of the development in N surplus from the landscape in DK from 1998–2008 showed a 22% reduction related to measures targeted at N emissions from livestock farms. Based on the large differences in N surplus between average N management farms and the most modern and N-efficient farms, it was concluded that additional N-surplus reductions of 25–50%, as compared to the present level, were realistic in all landscapes. The implemented N-surplus method was thus effective for comparing and synthesizing results on farm N emissions and the potentials of mitigation options. It is recommended for use in combination with other methods for the assessment of landscape N emissions and farm N efficiency, including more detailed N source and N sink hotspot mapping, measurements and modelling.

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Prediction at ungauged sites is essential for water resources planning and management. Ungauged sites have no observations about the magnitude of floods, but some site and basin characteristics are known. Regression models relate physiographic and climatic basin characteristics to flood quantiles, which can be estimated from observed data at gauged sites. However, these models assume linear relationships between variables Prediction intervals are estimated by the variance of the residuals in the estimated model. Furthermore, the effect of the uncertainties in the explanatory variables on the dependent variable cannot be assessed. This paper presents a methodology to propagate the uncertainties that arise in the process of predicting flood quantiles at ungauged basins by a regression model. In addition, Bayesian networks were explored as a feasible tool for predicting flood quantiles at ungauged sites. Bayesian networks benefit from taking into account uncertainties thanks to their probabilistic nature. They are able to capture non-linear relationships between variables and they give a probability distribution of discharges as result. The methodology was applied to a case study in the Tagus basin in Spain.

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This paper presents an operational concept for Air Traffic Management, and in particular arrival management, in which aircraft are permitted to operate in a manner consistent with current optimal aircraft operating techniques. The proposed concept allows aircraft to descend in the fuel efficient path managed mode and with arrival time not actively controlled. It will be demonstrated how the associated uncertainty in the time dimension of the trajectory can be managed through the application of multiple metering points strategically chosen along the trajectory. The proposed concept does not make assumptions on aircraft equipage (e.g. time of arrival control), but aims at handling mixed-equipage scenarios that most likely will remain far into the next decade and arguably beyond.

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This paper presents a methodology and algorithm for Air Traffic Control (ATC) to efficiently achieve schedules arrival times through speed control in the presence of uncertainty. The methodology does not assume the availability of airborne time of arrival control and can therefore be applied to legacy aircraft. The speed advisories are calculated in a manner that allows for sufficient control margin to, if required, adjust the aircraft's trajectory at a later stage to correct for estimated arrival time drift at the lowest impact to efficiency. The methodology is therefore envisioned to prevent major last-minute interventions and instead assists ATC in allowing more continuous descent approaches to be conducted by aircraft leading to more efficient operations.

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La gestión del tráfico aéreo (Air Traffic Management, ATM) está experimentando un cambio de paradigma hacia las denominadas operaciones basadas trayectoria. Bajo dicho paradigma se modifica el papel de los controladores de tráfico aéreo desde una operativa basada su intervención táctica continuada hacia una labor de supervisión a más largo plazo. Esto se apoya en la creciente confianza en las soluciones aportadas por las herramientas automatizadas de soporte a la decisión más modernas. Para dar soporte a este concepto, se precisa una importante inversión para el desarrollo, junto con la adquisición de nuevos equipos en tierra y embarcados, que permitan la sincronización precisa de la visión de la trayectoria, basada en el intercambio de información entre ambos actores. Durante los últimos 30 a 40 años las aerolíneas han generado uno de los menores retornos de la inversión de entre todas las industrias. Sin beneficios tangibles, la industria aérea tiene dificultades para atraer el capital requerido para su modernización, lo que retrasa la implantación de dichas mejoras. Esta tesis tiene como objetivo responder a la pregunta de si las capacidades actualmente instaladas en las aeronaves comerciales se pueden aplicar para lograr la sincronización de la trayectoria con el nivel de calidad requerido. Además, se analiza en ella si, conjuntamente con mejoras en las herramientas de predicción trayectorias instaladas en tierra en para facilitar la gestión de las arribadas, dichas capacidades permiten obtener los beneficios esperados en el marco de las operaciones basadas en trayectoria. Esto podría proporcionar un incentivo para futuras actualizaciones de la aviónica que podrían llevar a mejoras adicionales. El concepto operacional propuesto en esta tesis tiene como objetivo permitir que los aviones sean pilotados de una manera consistente con las técnicas actuales de vuelo optimizado. Se permite a las aeronaves que desciendan en el denominado “modo de ángulo de descenso gestionado” (path-managed mode), que es el preferido por la mayoría de las compañías aéreas, debido a que conlleva un reducido consumo de combustible. El problema de este modo es que en él no se controla de forma activa el tiempo de llegada al punto de interés. En nuestro concepto operacional, la incertidumbre temporal se gestiona en mediante de la medición del tiempo en puntos estratégicamente escogidos a lo largo de la trayectoria de la aeronave, y permitiendo la modificación por el control de tierra de la velocidad de la aeronave. Aunque la base del concepto es la gestión de las ordenes de velocidad que se proporcionan al piloto, para ser capaces de operar con los niveles de equipamiento típicos actualmente, dicho concepto también constituye un marco en el que la aviónica más avanzada (por ejemplo, que permita el control por el FMS del tiempo de llegada) puede integrarse de forma natural, una vez que esta tecnología este instalada. Además de gestionar la incertidumbre temporal a través de la medición en múltiples puntos, se intenta reducir dicha incertidumbre al mínimo mediante la mejora de las herramienta de predicción de la trayectoria en tierra. En esta tesis se presenta una novedosa descomposición del proceso de predicción de trayectorias en dos etapas. Dicha descomposición permite integrar adecuadamente los datos de la trayectoria de referencia calculada por el Flight Management System (FMS), disponibles usando Futuro Sistema de Navegación Aérea (FANS), en el sistema de predicción de trayectorias en tierra. FANS es un equipo presente en los aviones comerciales de fuselaje ancho actualmente en la producción, e incluso algunos aviones de fuselaje estrecho pueden tener instalada avionica FANS. Además de informar automáticamente de la posición de la aeronave, FANS permite proporcionar (parte de) la trayectoria de referencia en poder de los FMS, pero la explotación de esta capacidad para la mejora de la predicción de trayectorias no se ha estudiado en profundidad en el pasado. La predicción en dos etapas proporciona una solución adecuada al problema de sincronización de trayectorias aire-tierra dado que permite la sincronización de las dimensiones controladas por el sistema de guiado utilizando la información de la trayectoria de referencia proporcionada mediante FANS, y también facilita la mejora en la predicción de las dimensiones abiertas restantes usado un modelo del guiado que explota los modelos meteorológicos mejorados disponibles en tierra. Este proceso de predicción de la trayectoria de dos etapas se aplicó a una muestra de 438 vuelos reales que realizaron un descenso continuo (sin intervención del controlador) con destino Melbourne. Dichos vuelos son de aeronaves del modelo Boeing 737-800, si bien la metodología descrita es extrapolable a otros tipos de aeronave. El método propuesto de predicción de trayectorias permite una mejora en la desviación estándar del error de la estimación del tiempo de llegada al punto de interés, que es un 30% menor que la que obtiene el FMS. Dicha trayectoria prevista mejorada se puede utilizar para establecer la secuencia de arribadas y para la asignación de las franjas horarias para cada aterrizaje (slots). Sobre la base del slot asignado, se determina un perfil de velocidades que permita cumplir con dicho slot con un impacto mínimo en la eficiencia del vuelo. En la tesis se propone un nuevo algoritmo que determina las velocidades requeridas sin necesidad de un proceso iterativo de búsqueda sobre el sistema de predicción de trayectorias. El algoritmo se basa en una parametrización inteligente del proceso de predicción de la trayectoria, que permite relacionar el tiempo estimado de llegada con una función polinómica. Resolviendo dicho polinomio para el tiempo de llegada deseado, se obtiene de forma natural el perfil de velocidades optimo para cumplir con dicho tiempo de llegada sin comprometer la eficiencia. El diseño de los sistemas de gestión de arribadas propuesto en esta tesis aprovecha la aviónica y los sistemas de comunicación instalados de un modo mucho más eficiente, proporcionando valor añadido para la industria. Por tanto, la solución es compatible con la transición hacia los sistemas de aviónica avanzados que están desarrollándose actualmente. Los beneficios que se obtengan a lo largo de dicha transición son un incentivo para inversiones subsiguientes en la aviónica y en los sistemas de control de tráfico en tierra. ABSTRACT Air traffic management (ATM) is undergoing a paradigm shift towards trajectory based operations where the role of an air traffic controller evolves from that of continuous intervention towards supervision, as decision making is improved based on increased confidence in the solutions provided by advanced automation. To support this concept, significant investment for the development and acquisition of new equipment is required on the ground as well as in the air, to facilitate the high degree of trajectory synchronisation and information exchange required. Over the past 30-40 years the airline industry has generated one of the lowest returns on invested capital among all industries. Without tangible benefits realised, the airline industry may find it difficult to attract the required investment capital and delay acquiring equipment needed to realise the concept of trajectory based operations. In response to these challenges facing the modernisation of ATM, this thesis aims to answer the question whether existing aircraft capabilities can be applied to achieve sufficient trajectory synchronisation and improvements to ground-based trajectory prediction in support of the arrival management process, to realise some of the benefits envisioned under trajectory based operations, and to provide an incentive for further avionics upgrades. The proposed operational concept aims to permit aircraft to operate in a manner consistent with current optimal aircraft operating techniques. It allows aircraft to descend in the fuel efficient path managed mode as preferred by a majority of airlines, with arrival time not actively controlled by the airborne automation. The temporal uncertainty is managed through metering at strategically chosen points along the aircraft’s trajectory with primary use of speed advisories. While the focus is on speed advisories to support all aircraft and different levels of equipage, the concept also constitutes a framework in which advanced avionics as airborne time-of-arrival control can be integrated once this technology is widely available. In addition to managing temporal uncertainty through metering at multiple points, this temporal uncertainty is minimised by improving the supporting trajectory prediction capability. A novel two-stage trajectory prediction process is presented to adequately integrate aircraft trajectory data available through Future Air Navigation Systems (FANS) into the ground-based trajectory predictor. FANS is standard equipment on any wide-body aircraft in production today, and some single-aisle aircraft are easily capable of being fitted with FANS. In addition to automatic position reporting, FANS provides the ability to provide (part of) the reference trajectory held by the aircraft’s Flight Management System (FMS), but this capability has yet been widely overlooked. The two-stage process provides a ‘best of both world’s’ solution to the air-ground synchronisation problem by synchronising with the FMS reference trajectory those dimensions controlled by the guidance mode, and improving on the prediction of the remaining open dimensions by exploiting the high resolution meteorological forecast available to a ground-based system. The two-stage trajectory prediction process was applied to a sample of 438 FANS-equipped Boeing 737-800 flights into Melbourne conducting a continuous descent free from ATC intervention, and can be extrapolated to other types of aircraft. Trajectories predicted through the two-stage approach provided estimated time of arrivals with a 30% reduction in standard deviation of the error compared to estimated time of arrival calculated by the FMS. This improved predicted trajectory can subsequently be used to set the sequence and allocate landing slots. Based on the allocated landing slot, the proposed system calculates a speed schedule for the aircraft to meet this landing slot at minimal flight efficiency impact. A novel algorithm is presented that determines this speed schedule without requiring an iterative process in which multiple calls to a trajectory predictor need to be made. The algorithm is based on parameterisation of the trajectory prediction process, allowing the estimate time of arrival to be represented by a polynomial function of the speed schedule, providing an analytical solution to the speed schedule required to meet a set arrival time. The arrival management solution proposed in this thesis leverages the use of existing avionics and communications systems resulting in new value for industry for current investment. The solution therefore supports a transition concept from mixed equipage towards advanced avionics currently under development. Benefits realised under this transition may provide an incentive for ongoing investment in avionics.

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El objetivo de esta investigación consiste en definir un modelo de reserva de capacidad, por analogías con emergencias hospitalarias, que pueda ser implementado en el sector de servicios. Este está específicamente enfocado a su aplicación en talleres de servicio de automóviles. Nuestra investigación incorpora la incertidumbre de la demanda en un modelo singular diseñado en etapas que agrupa técnicas ARIMA, teoría de colas y simulación Monte Carlo para definir los conceptos de capacidad y ocupación de servicio, que serán utilizados para minimizar el coste implícito de la reserva capacidad necesaria para atender a clientes que carecen de cita previa. Habitualmente, las compañías automovilísticas estiman la capacidad de sus instalaciones de servicio empíricamente, pero los clientes pueden llegar bajo condiciones de incertidumbre que no se tienen en cuenta en dichas estimaciones, por lo que existe una diferencia entre lo que el cliente realmente demanda y la capacidad que ofrece el servicio. Nuestro enfoque define una metodología válida para el sector automovilístico que cubre la ausencia genérica de investigaciones recientes y la habitual falta de aplicación de técnicas estadísticas en el sector. La equivalencia con la gestión de urgencias hospitalarias se ha validado a lo largo de la investigación en la se definen nuevos indicadores de proceso (KPIs) Tal y como hacen los hospitales, aplicamos modelos estocásticos para dimensionar las instalaciones de servicio de acuerdo con la distribución demográfica del área de influencia. El modelo final propuesto integra la predicción del coste implícito en la reserva de capacidad para atender la demanda no prevista. Asimismo, se ha desarrollado un código en Matlab que puede integrarse como un módulo adicional a los sistemas de información (DMS) que se usan actualmente en el sector, con el fin de emplear los nuevos indicadores de proceso definidos en el modelo. Los resultados principales del modelo son nuevos indicadores de servicio, tales como la capacidad, ocupación y coste de reserva de capacidad, que nunca antes han sido objeto de estudio en la industria automovilística, y que están orientados a gestionar la operativa del servicio. ABSTRACT Our aim is to define a Capacity Reserve model to be implemented in the service sector by hospital's emergency room (ER) analogies, with a practical approach to passenger car services. A stochastic model has been implemented using R and a Monte Carlo simulation code written in Matlab and has proved a very useful tool for optimal decision making under uncertainty. The research integrates demand uncertainty in a unique model which is built in stages by implementing ARIMA forecasting, Queuing Theory and a Monte Carlo simulation to define the concepts of service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Usually, passenger car companies estimate their service facilities capacity using empirical methods, but customers arrive under uncertain conditions not included in the estimations. Thus, there is a gap between customer’s real demand and the dealer’s capacity. This research sets a valid methodology for the passenger car industry to cover the generic absence of recent researches and the generic lack of statistical techniques implementation. The hospital’s emergency room (ER) equalization has been confirmed to be valid for the passenger car industry and new process indicators have been defined to support the study. As hospitals do, we aim to apply stochastic models to dimension installations according to the demographic distribution of the area to be serviced. The proposed model integrates the prediction of the cost implicit in the reserve capacity to serve unexpected demand. The Matlab code could be implemented as part of the existing information technology systems (ITs) to support the existing service management tools, creating a set of new process indicators. Main model outputs are new indicators, such us Capacity, Occupancy and Cost of Capacity Reserve, never studied in the passenger car service industry before, and intended to manage the service operation.

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PURPOSE The decision-making process plays a key role in organizations. Every decision-making process produces a final choice that may or may not prompt action. Recurrently, decision makers find themselves in the dichotomous question of following a traditional sequence decision-making process where the output of a decision is used as the input of the next stage of the decision, or following a joint decision-making approach where several decisions are taken simultaneously. The implication of the decision-making process will impact different players of the organization. The choice of the decision- making approach becomes difficult to find, even with the current literature and practitioners’ knowledge. The pursuit of better ways for making decisions has been a common goal for academics and practitioners. Management scientists use different techniques and approaches to improve different types of decisions. The purpose of this decision is to use the available resources as well as possible (data and techniques) to achieve the objectives of the organization. The developing and applying of models and concepts may be helpful to solve managerial problems faced every day in different companies. As a result of this research different decision models are presented to contribute to the body of knowledge of management science. The first models are focused on the manufacturing industry and the second part of the models on the health care industry. Despite these models being case specific, they serve the purpose of exemplifying that different approaches to the problems and could provide interesting results. Unfortunately, there is no universal recipe that could be applied to all the problems. Furthermore, the same model could deliver good results with certain data and bad results for other data. A framework to analyse the data before selecting the model to be used is presented and tested in the models developed to exemplify the ideas. METHODOLOGY As the first step of the research a systematic literature review on the joint decision is presented, as are the different opinions and suggestions of different scholars. For the next stage of the thesis, the decision-making process of more than 50 companies was analysed in companies from different sectors in the production planning area at the Job Shop level. The data was obtained using surveys and face-to-face interviews. The following part of the research into the decision-making process was held in two application fields that are highly relevant for our society; manufacturing and health care. The first step was to study the interactions and develop a mathematical model for the replenishment of the car assembly where the problem of “Vehicle routing problem and Inventory” were combined. The next step was to add the scheduling or car production (car sequencing) decision and use some metaheuristics such as ant colony and genetic algorithms to measure if the behaviour is kept up with different case size problems. A similar approach is presented in a production of semiconductors and aviation parts, where a hoist has to change from one station to another to deal with the work, and a jobs schedule has to be done. However, for this problem simulation was used for experimentation. In parallel, the scheduling of operating rooms was studied. Surgeries were allocated to surgeons and the scheduling of operating rooms was analysed. The first part of the research was done in a Teaching hospital, and for the second part the interaction of uncertainty was added. Once the previous problem had been analysed a general framework to characterize the instance was built. In the final chapter a general conclusion is presented. FINDINGS AND PRACTICAL IMPLICATIONS The first part of the contributions is an update of the decision-making literature review. Also an analysis of the possible savings resulting from a change in the decision process is made. Then, the results of the survey, which present a lack of consistency between what the managers believe and the reality of the integration of their decisions. In the next stage of the thesis, a contribution to the body of knowledge of the operation research, with the joint solution of the replenishment, sequencing and inventory problem in the assembly line is made, together with a parallel work with the operating rooms scheduling where different solutions approaches are presented. In addition to the contribution of the solving methods, with the use of different techniques, the main contribution is the framework that is proposed to pre-evaluate the problem before thinking of the techniques to solve it. However, there is no straightforward answer as to whether it is better to have joint or sequential solutions. Following the proposed framework with the evaluation of factors such as the flexibility of the answer, the number of actors, and the tightness of the data, give us important hints as to the most suitable direction to take to tackle the problem. RESEARCH LIMITATIONS AND AVENUES FOR FUTURE RESEARCH In the first part of the work it was really complicated to calculate the possible savings of different projects, since in many papers these quantities are not reported or the impact is based on non-quantifiable benefits. The other issue is the confidentiality of many projects where the data cannot be presented. For the car assembly line problem more computational power would allow us to solve bigger instances. For the operation research problem there was a lack of historical data to perform a parallel analysis in the teaching hospital. In order to keep testing the decision framework it is necessary to keep applying more case studies in order to generalize the results and make them more evident and less ambiguous. The health care field offers great opportunities since despite the recent awareness of the need to improve the decision-making process there are many opportunities to improve. Another big difference with the automotive industry is that the last improvements are not spread among all the actors. Therefore, in the future this research will focus more on the collaboration between academia and the health care sector.