MRI texture analysis as means for addressing rehydration and milk diffusion of cereals

Cereals microstructure is one of the primary quality attributes of cereals. Cereals rehydration and milk diffusion depends on such microstructure and thus, the crispiness and the texture, which will make it more palatable for the final consumer. Magnetic Resonance Imaging (MRI) is a very powerful topographic tool since acquisition parameter leads to a wide possibility for identifying textures, structures and liquids mobility. It is suited for non-invasive imaging of water and fats. Rehydration and diffusion cereals processes were measured by MRI at different times and using two different kinds of milk, varying their fat level. Several images were obtained. A combination of textural analysis (based on the analysis of histograms) and segmentation methods (in order to understand the rehydration level of each variety of cereals) were performed. According to the rehydration level, no advisable clustering behavior was found. Nevertheless, some differences were noticeable between the coating, the type of milk and the variety of cereals

Diffusion of Zn into GaAs and AlGaAs from isothermal Liquid-phase epitaxy solutions

In this work we present results of zinc diffusion in GaAs using the liquid phase epitaxy technique from liquid solutions of Ga‐As‐Zn and Ga‐As‐Al‐Zn. Using silicon‐doped n‐GaAs substrates, working at a diffusion temperature of 850 °C, and introducing a dopant concentration ranging 1018–1019 cm−3, the most important findings regarding the diffusion properties are as follows: (a) zinc concentration in the solid depends on the square root of zinc atomic fraction in the liquid; (b) the diffusion is dominated by the interstitial‐substitutional process; (c) the diffusivity D varies as about C3 in the form D=2.9×10−67C3.05; (d) aluminum plays the role of the catalyst of the diffusion process, if it is introduced in the liquid solution, since it is found that D varies as (γAsXlAs)−1; (e) the zinc interstitial is mainly doubly ionized (Zn++i); (f) the zinc diffusion coefficient in Al0.85 Ga0.15 As is about four times greater than in GaAs; (g) by means of all these results, it is possible to control zinc diffusion processes in order to obtain optimized depth junctions and doping levels in semiconductor device fabrication.

Modelling diffusion of photovoltaic: concepts and applications

Innovation studies have been interest of not only the scholars from various fields such as economics, management and sociology but also industrial practitioners and policy makers. In this vast and fruitful field, the theory of diffusion of innovations, which has been driven by a sociological approach, has played a vital role in our understanding of the mechanisms behind industrial change. In this paper, our aim is to give a state of art review of diffusion of innovation models in a structural and conceptual way with special reference to photovoltaic. We argue firstly, as an underlying background, how diffusion of innovations theory differs from other innovation studies. Secondly we give a brief taxonomical review of modelling methodologies together with comparative discussions. And finally we put the wealth of modelling in the context of photovoltaic diffusion and suggest some future directions.

Diffusion of photovoltaic in Germany: policy vs. consumers

In some countries photovoltaic (PV) technology has already achieved a stage of development at which it can compete with conventional electricity sources. Germany provides a good illustration of this where PV market has reached a mature stage. As a manifest of this, the German government has recently reduced subsidies for households and industry by decreasing the feed in tariff for PV. This development raises fundamental questions: could the PV industry survive? Will consumers be motivated to continue to adopt PV when feed-in tariff diminish? The point of departure for the relevant literature on diffusion of PV has been on the effect of subsidies but little attention has paid to consumer motives when the policy support is scaled down. This paper introduces an in-depth analysis on understanding the consumer motives for adopting photovoltaic applications. Anchored in an extensive exploratory case study on PV consumers and PV system providers, this study aims to provide an encompassing explanation of diffusion of PV by revealing the link between consumer motives and the impact of policy.

Diffusion of Eco-innovations: exploring the literature

In recent years, the importance of the management of eco-innovations has been growing, more in practice than in academia. However, although in the literature there are already some evidences focussed on management of eco-innovations, there is no comprehensive review on the knowledge base of diffusion of eco-innovations. This paper provides a current overview of the existing body of literature, identifying the most active scholars and relevant publications in this field, and deepening in the major disciplines and research streams. Results show that the theory of diffusion of innovations which provided the philosophical underpinnings of how innovations are diffused is not the main knowledge base to explain the diffusion of eco-innovations. Lead market hypothesis, sustainable transitions and the ecological modernization appear as the initial base of the cognitive platform that can contribute to the understanding of diffusion of eco-innovations.

Diffusion of photovoltaic in Germany: roles of policy, system suppliers and adopters

In some countries photovoltaic (PV) technology is at a stage of development at which it can compete with conventional electricity sources. A case in point is Germany where PV market has reached a mature stage. As a manifest of this, the German government has recently reduced the feed-in-tariff, which had been the strongest driver of PV diffusion. This development raises a fundamental question: Why would potential adopters be motivated to adopt PV when feed-in tariff diminishes? The point of departure for the literature on diffusion of PV has been on the effect of subsidies but little attention has paid to adopter motives when the policy support is scaled down. This paper presents an in-depth analysis of the adopter motives for photovoltaic applications. Anchored in an extensive exploratory case study we provide an encompassing explanation of roles of policy, adopters and system suppliers on diffusion of PV.

Thermal diffusion profile by NRA of Deuterium implanted in solid breeder blanket materials

This paper studies the relationship between aging, physical changes and the results of non-destructive testing of plywood. 176 pieces of plywood were tested to analyze their actual and estimated density using non-destructive methods (screw withdrawal force and ultrasound wave velocity) during a laboratory aging test. From the results of statistical analysis it can be concluded that there is a strong relationship between the non-destructive measurements carried out, and the decline in the physical properties of the panels due to aging. The authors propose several models to estimate board density. The best results are obtained with ultrasound. A reliable prediction of the degree of deterioration (aging) of board is presented. Breeder blanket materials have to produce tritium from lithium while fulfilling several strict conditions. In particular, when dealing with materials to be applied in fusion reactors, one of the key questions is the study of light ions retention, which can be produced by transmutation reactions and/or introduced by interaction with the plasma. In ceramic breeders the understanding of the hydrogen isotopes behaviour and specially the diffusion of tritium to the surface is crucial. Moreover the evolution of the microstructure during irradiation with energetic ions, neutrons and electrons is complex because of the interaction of a high number of processes.

Intelligent context-aware services based on internet of things architectures

La Internet de las Cosas (IoT), como parte de la Futura Internet, se ha convertido en la actualidad en uno de los principales temas de investigación; en parte gracias a la atención que la sociedad está poniendo en el desarrollo de determinado tipo de servicios (telemetría, generación inteligente de energía, telesanidad, etc.) y por las recientes previsiones económicas que sitúan a algunos actores, como los operadores de telecomunicaciones (que se encuentran desesperadamente buscando nuevas oportunidades), al frente empujando algunas tecnologías interrelacionadas como las comunicaciones Máquina a Máquina (M2M). En este contexto, un importante número de actividades de investigación a nivel mundial se están realizando en distintas facetas: comunicaciones de redes de sensores, procesado de información, almacenamiento de grandes cantidades de datos (big--‐data), semántica, arquitecturas de servicio, etc. Todas ellas, de forma independiente, están llegando a un nivel de madurez que permiten vislumbrar la realización de la Internet de las Cosas más que como un sueño, como una realidad tangible. Sin embargo, los servicios anteriormente mencionados no pueden esperar a desarrollarse hasta que las actividades de investigación obtengan soluciones holísticas completas. Es importante proporcionar resultados intermedios que eviten soluciones verticales realizadas para desarrollos particulares. En este trabajo, nos hemos focalizado en la creación de una plataforma de servicios que pretende facilitar, por una parte la integración de redes de sensores y actuadores heterogéneas y geográficamente distribuidas, y por otra lado el desarrollo de servicios horizontales utilizando dichas redes y la información que proporcionan. Este habilitador se utilizará para el desarrollo de servicios y para la experimentación en la Internet de las Cosas. Previo a la definición de la plataforma, se ha realizado un importante estudio focalizando no sólo trabajos y proyectos de investigación, sino también actividades de estandarización. Los resultados se pueden resumir en las siguientes aseveraciones: a) Los modelos de datos definidos por el grupo “Sensor Web Enablement” (SWE™) del “Open Geospatial Consortium (OGC®)” representan hoy en día la solución más completa para describir las redes de sensores y actuadores así como las observaciones. b) Las interfaces OGC, a pesar de las limitaciones que requieren cambios y extensiones, podrían ser utilizadas como las bases para acceder a sensores y datos. c) Las redes de nueva generación (NGN) ofrecen un buen sustrato que facilita la integración de redes de sensores y el desarrollo de servicios. En consecuencia, una nueva plataforma de Servicios, llamada Ubiquitous Sensor Networks (USN), se ha definido en esta Tesis tratando de contribuir a rellenar los huecos previamente mencionados. Los puntos más destacados de la plataforma USN son: a) Desde un punto de vista arquitectónico, sigue una aproximación de dos niveles (Habilitador y Gateway) similar a otros habilitadores que utilizan las NGN (como el OMA Presence). b) Los modelos de datos están basado en los estándares del OGC SWE. iv c) Está integrado en las NGN pero puede ser utilizado sin ellas utilizando infraestructuras IP abiertas. d) Las principales funciones son: Descubrimiento de sensores, Almacenamiento de observaciones, Publicacion--‐subscripcion--‐notificación, ejecución remota homogénea, seguridad, gestión de diccionarios de datos, facilidades de monitorización, utilidades de conversión de protocolos, interacciones síncronas y asíncronas, soporte para el “streaming” y arbitrado básico de recursos. Para demostrar las funcionalidades que la Plataforma USN propuesta pueden ofrecer a los futuros escenarios de la Internet de las Cosas, se presentan resultados experimentales de tres pruebas de concepto (telemetría, “Smart Places” y monitorización medioambiental) reales a pequeña escala y un estudio sobre semántica (sistema de información vehicular). Además, se está utilizando actualmente como Habilitador para desarrollar tanto experimentación como servicios reales en el proyecto Europeo SmartSantander (que aspira a integrar alrededor de 20.000 dispositivos IoT). v Abstract Internet of Things, as part of the Future Internet, has become one of the main research topics nowadays; in part thanks to the pressure the society is putting on the development of a particular kind of services (Smart metering, Smart Grids, eHealth, etc.), and by the recent business forecasts that situate some players, like Telecom Operators (which are desperately seeking for new opportunities), at the forefront pushing for some interrelated technologies like Machine--‐to--‐Machine (M2M) communications. Under this context, an important number of research activities are currently taking place worldwide at different levels: sensor network communications, information processing, big--‐ data storage, semantics, service level architectures, etc. All of them, isolated, are arriving to a level of maturity that envision the achievement of Internet of Things (IoT) more than a dream, a tangible goal. However, the aforementioned services cannot wait to be developed until the holistic research actions bring complete solutions. It is important to come out with intermediate results that avoid vertical solutions tailored for particular deployments. In the present work, we focus on the creation of a Service--‐level platform intended to facilitate, from one side the integration of heterogeneous and geographically disperse Sensors and Actuator Networks (SANs), and from the other the development of horizontal services using them and the information they provide. This enabler will be used for horizontal service development and for IoT experimentation. Prior to the definition of the platform, we have realized an important study targeting not just research works and projects, but also standardization topics. The results can be summarized in the following assertions: a) Open Geospatial Consortium (OGC®) Sensor Web Enablement (SWE™) data models today represent the most complete solution to describe SANs and observations. b) OGC interfaces, despite the limitations that require changes and extensions, could be used as the bases for accessing sensors and data. c) Next Generation Networks (NGN) offer a good substrate that facilitates the integration of SANs and the development of services. Consequently a new Service Layer platform, called Ubiquitous Sensor Networks (USN), has been defined in this Thesis trying to contribute to fill in the previous gaps. The main highlights of the proposed USN Platform are: a) From an architectural point of view, it follows a two--‐layer approach (Enabler and Gateway) similar to other enablers that run on top of NGN (like the OMA Presence). b) Data models and interfaces are based on the OGC SWE standards. c) It is integrated in NGN but it can be used without it over open IP infrastructures. d) Main functions are: Sensor Discovery, Observation Storage, Publish--‐Subscribe--‐Notify, homogeneous remote execution, security, data dictionaries handling, monitoring facilities, authorization support, protocol conversion utilities, synchronous and asynchronous interactions, streaming support and basic resource arbitration. vi In order to demonstrate the functionalities that the proposed USN Platform can offer to future IoT scenarios, some experimental results have been addressed in three real--‐life small--‐scale proofs--‐of concepts (Smart Metering, Smart Places and Environmental monitoring) and a study for semantics (in--‐vehicle information system). Furthermore we also present the current use of the proposed USN Platform as an Enabler to develop experimentation and real services in the SmartSantander EU project (that aims at integrating around 20.000 IoT devices).

Análisis y modelización de la dinámica emergente durante el proceso de difusión de información en las redes sociales de internet

Durante la actividad diaria, la sociedad actual interactúa constantemente por medio de dispositivos electrónicos y servicios de telecomunicaciones, tales como el teléfono, correo electrónico, transacciones bancarias o redes sociales de Internet. Sin saberlo, masivamente dejamos rastros de nuestra actividad en las bases de datos de empresas proveedoras de servicios. Estas nuevas fuentes de datos tienen las dimensiones necesarias para que se puedan observar patrones de comportamiento humano a grandes escalas. Como resultado, ha surgido una reciente explosión sin precedentes de estudios de sistemas sociales, dirigidos por el análisis de datos y procesos computacionales. En esta tesis desarrollamos métodos computacionales y matemáticos para analizar sistemas sociales por medio del estudio combinado de datos derivados de la actividad humana y la teoría de redes complejas. Nuestro objetivo es caracterizar y entender los sistemas emergentes de interacciones sociales en los nuevos espacios tecnológicos, tales como la red social Twitter y la telefonía móvil. Analizamos los sistemas por medio de la construcción de redes complejas y series temporales, estudiando su estructura, funcionamiento y evolución en el tiempo. También, investigamos la naturaleza de los patrones observados por medio de los mecanismos que rigen las interacciones entre individuos, así como medimos el impacto de eventos críticos en el comportamiento del sistema. Para ello, hemos propuesto modelos que explican las estructuras globales y la dinámica emergente con que fluye la información en el sistema. Para los estudios de la red social Twitter, hemos basado nuestros análisis en conversaciones puntuales, tales como protestas políticas, grandes acontecimientos o procesos electorales. A partir de los mensajes de las conversaciones, identificamos a los usuarios que participan y construimos redes de interacciones entre los mismos. Específicamente, construimos una red para representar quién recibe los mensajes de quién y otra red para representar quién propaga los mensajes de quién. En general, hemos encontrado que estas estructuras tienen propiedades complejas, tales como crecimiento explosivo y distribuciones de grado libres de escala. En base a la topología de estas redes, hemos indentificado tres tipos de usuarios que determinan el flujo de información según su actividad e influencia. Para medir la influencia de los usuarios en las conversaciones, hemos introducido una nueva medida llamada eficiencia de usuario. La eficiencia se define como el número de retransmisiones obtenidas por mensaje enviado, y mide los efectos que tienen los esfuerzos individuales sobre la reacción colectiva. Hemos observado que la distribución de esta propiedad es ubicua en varias conversaciones de Twitter, sin importar sus dimensiones ni contextos. Con lo cual, sugerimos que existe universalidad en la relación entre esfuerzos individuales y reacciones colectivas en Twitter. Para explicar los factores que determinan la emergencia de la distribución de eficiencia, hemos desarrollado un modelo computacional que simula la propagación de mensajes en la red social de Twitter, basado en el mecanismo de cascadas independientes. Este modelo nos permite medir el efecto que tienen sobre la distribución de eficiencia, tanto la topología de la red social subyacente, como la forma en que los usuarios envían mensajes. Los resultados indican que la emergencia de un grupo selecto de usuarios altamente eficientes depende de la heterogeneidad de la red subyacente y no del comportamiento individual. Por otro lado, hemos desarrollado técnicas para inferir el grado de polarización política en redes sociales. Proponemos una metodología para estimar opiniones en redes sociales y medir el grado de polarización en las opiniones obtenidas. Hemos diseñado un modelo donde estudiamos el efecto que tiene la opinión de un pequeño grupo de usuarios influyentes, llamado élite, sobre las opiniones de la mayoría de usuarios. El modelo da como resultado una distribución de opiniones sobre la cual medimos el grado de polarización. Aplicamos nuestra metodología para medir la polarización en redes de difusión de mensajes, durante una conversación en Twitter de una sociedad políticamente polarizada. Los resultados obtenidos presentan una alta correspondencia con los datos offline. Con este estudio, hemos demostrado que la metodología propuesta es capaz de determinar diferentes grados de polarización dependiendo de la estructura de la red. Finalmente, hemos estudiado el comportamiento humano a partir de datos de telefonía móvil. Por una parte, hemos caracterizado el impacto que tienen desastres naturales, como innundaciones, sobre el comportamiento colectivo. Encontramos que los patrones de comunicación se alteran de forma abrupta en las áreas afectadas por la catástofre. Con lo cual, demostramos que se podría medir el impacto en la región casi en tiempo real y sin necesidad de desplegar esfuerzos en el terreno. Por otra parte, hemos estudiado los patrones de actividad y movilidad humana para caracterizar las interacciones entre regiones de un país en desarrollo. Encontramos que las redes de llamadas y trayectorias humanas tienen estructuras de comunidades asociadas a regiones y centros urbanos. En resumen, hemos mostrado que es posible entender procesos sociales complejos por medio del análisis de datos de actividad humana y la teoría de redes complejas. A lo largo de la tesis, hemos comprobado que fenómenos sociales como la influencia, polarización política o reacción a eventos críticos quedan reflejados en los patrones estructurales y dinámicos que presentan la redes construidas a partir de datos de conversaciones en redes sociales de Internet o telefonía móvil. ABSTRACT During daily routines, we are constantly interacting with electronic devices and telecommunication services. Unconsciously, we are massively leaving traces of our activity in the service providers’ databases. These new data sources have the dimensions required to enable the observation of human behavioral patterns at large scales. As a result, there has been an unprecedented explosion of data-driven social research. In this thesis, we develop computational and mathematical methods to analyze social systems by means of the combined study of human activity data and the theory of complex networks. Our goal is to characterize and understand the emergent systems from human interactions on the new technological spaces, such as the online social network Twitter and mobile phones. We analyze systems by means of the construction of complex networks and temporal series, studying their structure, functioning and temporal evolution. We also investigate on the nature of the observed patterns, by means of the mechanisms that rule the interactions among individuals, as well as on the impact of critical events on the system’s behavior. For this purpose, we have proposed models that explain the global structures and the emergent dynamics of information flow in the system. In the studies of the online social network Twitter, we have based our analysis on specific conversations, such as political protests, important announcements and electoral processes. From the messages related to the conversations, we identify the participant users and build networks of interactions with them. We specifically build one network to represent whoreceives- whose-messages and another to represent who-propagates-whose-messages. In general, we have found that these structures have complex properties, such as explosive growth and scale-free degree distributions. Based on the topological properties of these networks, we have identified three types of user behavior that determine the information flow dynamics due to their influence. In order to measure the users’ influence on the conversations, we have introduced a new measure called user efficiency. It is defined as the number of retransmissions obtained by message posted, and it measures the effects of the individual activity on the collective reacixtions. We have observed that the probability distribution of this property is ubiquitous across several Twitter conversation, regardlessly of their dimension or social context. Therefore, we suggest that there is a universal behavior in the relationship between individual efforts and collective reactions on Twitter. In order to explain the different factors that determine the user efficiency distribution, we have developed a computational model to simulate the diffusion of messages on Twitter, based on the mechanism of independent cascades. This model, allows us to measure the impact on the emergent efficiency distribution of the underlying network topology, as well as the way that users post messages. The results indicate that the emergence of an exclusive group of highly efficient users depends upon the heterogeneity of the underlying network instead of the individual behavior. Moreover, we have also developed techniques to infer the degree of polarization in social networks. We propose a methodology to estimate opinions in social networks and to measure the degree of polarization in the obtained opinions. We have designed a model to study the effects of the opinions of a small group of influential users, called elite, on the opinions of the majority of users. The model results in an opinions distribution to which we measure the degree of polarization. We apply our methodology to measure the polarization on graphs from the messages diffusion process, during a conversation on Twitter from a polarized society. The results are in very good agreement with offline and contextual data. With this study, we have shown that our methodology is capable of detecting several degrees of polarization depending on the structure of the networks. Finally, we have also inferred the human behavior from mobile phones’ data. On the one hand, we have characterized the impact of natural disasters, like flooding, on the collective behavior. We found that the communication patterns are abruptly altered in the areas affected by the catastrophe. Therefore, we demonstrate that we could measure the impact of the disaster on the region, almost in real-time and without needing to deploy further efforts. On the other hand, we have studied human activity and mobility patterns in order to characterize regional interactions on a developing country. We found that the calls and trajectories networks present community structure associated to regional and urban areas. In summary, we have shown that it is possible to understand complex social processes by means of analyzing human activity data and the theory of complex networks. Along the thesis, we have demonstrated that social phenomena, like influence, polarization and reaction to critical events, are reflected in the structural and dynamical patterns of the networks constructed from data regarding conversations on online social networks and mobile phones.

A survey of feature selection in Internet traffic characterization

In the last decade, the research community has focused on new classification methods that rely on statistical characteristics of Internet traffic, instead of pre-viously popular port-number-based or payload-based methods, which are under even bigger constrictions. Some research works based on statistical characteristics generated large fea-ture sets of Internet traffic; however, nowadays it?s impossible to handle hun-dreds of features in big data scenarios, only leading to unacceptable processing time and misleading classification results due to redundant and correlative data. As a consequence, a feature selection procedure is essential in the process of Internet traffic characterization. In this paper a survey of feature selection methods is presented: feature selection frameworks are introduced, and differ-ent categories of methods are briefly explained and compared; several proposals on feature selection in Internet traffic characterization are shown; finally, future application of feature selection to a concrete project is proposed.

A multi-level analysis of innovation diffusion: The case of solar photovoltaic systems in Germany and the disillusion of grid parity

¿Suministrarán las fuentes de energía renovables toda la energía que el mundo necesita algún día? Algunos argumentan que sí, mientras que otros dicen que no. Sin embargo, en algunas regiones del mundo, la producción de electricidad a través de fuentes de energía renovables ya está en una etapa prometedora de desarrollo en la que su costo de generación de electricidad compite con fuentes de electricidad convencionales, como por ejemplo la paridad de red. Este logro ha sido respaldado por el aumento de la eficiencia de la tecnología, la reducción de los costos de producción y, sobre todo, los años de intervenciones políticas de apoyo financiero. La difusión de los sistemas solares fotovoltaicos (PV) en Alemania es un ejemplo relevante. Alemania no sólo es el país líder en términos de capacidad instalada de sistemas fotovoltaicos (PV) en todo el mundo, sino también uno de los países pioneros donde la paridad de red se ha logrado recientemente. No obstante, podría haber una nube en el horizonte. La tasa de difusión ha comenzado a declinar en muchas regiones. Además, las empresas solares locales – que se sabe son importantes impulsores de la difusión – han comenzado a enfrentar dificultades para manejar sus negocios. Estos acontecimientos plantean algunas preguntas importantes: ¿Es ésta una disminución temporal en la difusión? ¿Los adoptantes continuarán instalando sistemas fotovoltaicos? ¿Qué pasa con los modelos de negocio de las empresas solares locales? Con base en el caso de los sistemas fotovoltaicos en Alemania a través de un análisis multinivel y dos revisiones literarias complementarias, esta tesis doctoral extiende el debate proporcionando riqueza múltiple de datos empíricos en un conocimiento de contexto limitado. El primer análisis se basa en la perspectiva del adoptante, que explora el nivel "micro" y el proceso social que subyace a la adopción de los sistemas fotovoltaicos. El segundo análisis es una perspectiva a nivel de empresa, que explora los modelos de negocio de las empresas y sus roles impulsores en la difusión de los sistemas fotovoltaicos. El tercero análisis es una perspectiva regional, la cual explora el nivel "meso", el proceso social que subyace a la adopción de sistemas fotovoltaicos y sus técnicas de modelado. Los resultados incluyen implicaciones tanto para académicos como políticos, no sólo sobre las innovaciones en energía renovable relativas a la paridad de red, sino también, de manera inductiva, sobre las innovaciones ambientales impulsadas por las políticas que logren la competitividad de costes. ABSTRACT Will renewable energy sources supply all of the world energy needs one day? Some argue yes, while others say no. However, in some regions of the world, the electricity production through renewable energy sources is already at a promising stage of development at which their electricity generation costs compete with conventional electricity sources’, i.e., grid parity. This achievement has been underpinned by the increase of technology efficiency, reduction of production costs and, above all, years of policy interventions of providing financial support. The diffusion of solar photovoltaic (PV) systems in Germany is an important frontrunner case in point. Germany is not only the top country in terms of installed PV systems’ capacity worldwide but also one of the pioneer countries where the grid parity has recently been achieved. However, there might be a cloud on the horizon. The diffusion rate has started to decline in many regions. In addition, local solar firms – which are known to be important drivers of diffusion – have started to face difficulties to run their businesses. These developments raise some important questions: Is this a temporary decline on diffusion? Will adopters continue to install PV systems? What about the business models of the local solar firms? Based on the case of PV systems in Germany through a multi-level analysis and two complementary literature reviews, this PhD Dissertation extends the debate by providing multiple wealth of empirical details in a context-limited knowledge. The first analysis is based on the adopter perspective, which explores the “micro” level and the social process underlying the adoption of PV systems. The second one is a firm-level perspective, which explores the business models of firms and their driving roles in diffusion of PV systems. The third one is a regional perspective, which explores the “meso” level, i.e., the social process underlying the adoption of PV systems and its modeling techniques. The results include implications for both scholars and policymakers, not only about renewable energy innovations at grid parity, but also in an inductive manner, about policy-driven environmental innovations that achieve the cost competiveness.

Finite Element Model of the Innovation Diffusion: An Application to Photovoltaic Systems

This paper presents a Finite Element Model, which has been used for forecasting the diffusion of innovations in time and space. Unlike conventional models used in diffusion literature, the model considers the spatial heterogeneity. The implementation steps of the model are explained by applying it to the case of diffusion of photovoltaic systems in a local region in southern Germany. The applied model is based on a parabolic partial differential equation that describes the diffusion ratio of photovoltaic systems in a given region over time. The results of the application show that the Finite Element Model constitutes a powerful tool to better understand the diffusion of an innovation as a simultaneous space-time process. For future research, model limitations and possible extensions are also discussed.