Knowledge-Production Processes in Practice Research - Outcomes and Critical Elements

The welfare sector has seen considerable changes in its operational context. Welfare services respond to an increasing number of challenges as citizens are confronted with life’s uncertainties and a variety of complex situations. At the same time the service-delivery system is facing problems of co-operation and the development of staff competence, as well as demands to improve service effectiveness and outcomes. In order to ensure optimal user outcomes in this complex, evolving environment it is necessary to enhance professional knowledge and skills, and to increase efforts to develop the services. Changes are also evident in the new emergent knowledge-production models. There has been a shift from knowledge acquisition and transmission to its construction and production. New actors have stepped in and the roles of researchers are subject to critical discussion. Research outcomes, in other words the usefulness of research with respect to practice development, is a topical agenda item. Research is needed, but if it is to be useful it needs to be not only credible but also useful in action. What do we know about different research processes in practice? What conceptions, approaches, methods and actor roles are embedded? What is the effect on practice? How does ‘here and now’ practice challenge research methods? This article is based on the research processes conducted in the institutes of practice research in social work in Finland. It analyses the different approaches applied by elucidating the theoretical standpoints and the critical elements embedded in them, and reflects on the outcomes in and for practice. It highlights the level of change and progression in practice research, arguing for diverse practice research models with a solid theoretical grounding, rigorous research processes, and a supportive infrastructure.

Social-Software-Portfolios im Einsatz

Die Dissertationsschrift widmet sich der Erforschung des Online-Lernens mittels Weblogs unter Anwendung der E-Portfolio Methode als einer seit mehreren Jahren verstärkt aufkommenden Lern- und Präsentationsform im Bildungskontext. Über mehrere Lehrveranstaltungen des Studiengangs "Angewandte Medien- und Kommunikationswissenschaft" an der Technischen Universität Ilmenau hinweg wurden drei Fallstudien gebildet. Innerhalb dieser wurde das Führen von eigenen E-Portfolio Blogs durch Studierende über einen Zeitraum von etwa drei Jahren evaluiert. Als Evaluationsziel wurde anhand spezifischer Fragestellungen ermittelt, wie das damit einhergehende selbstgesteuert-konnektive Lernen zu entsprechendem Erfolg führen kann. Hierbei wurde insbesondere die Teildimension Medienkompetenz im Spannungsfeld von Lernaktivität, Wissenserwerb und Informations-/Wissensmanagement betrachtet sowie weitere intervenierende Variablen, wie zum Beispiel Aufwand oder Akzeptanz, berücksichtigt. Inhaltlich wurden zunächst begriffliche Grundlagen dargestellt, die Nutzung von E-Portfolios in Theorie und Praxis beschrieben, Medienkompetenz-Ansätze detailliert aufgezeigt sowie in den Kontext von E-Portfolios gebracht und schließlich eine umfangreiche Analyse des Forschungsstandes aufbereitet. Diese gingen mit Erkenntnissen aus einer qualitativen Vorstudie in Form von fünf leitfadengestützten Experteninterviews einher. Die darauf aufbauende Hauptstudie widmete sich anschließend der Erhebung und Auswertung quantitativer Daten anhand von Online-Befragungen mit den Studierenden zu fünf Zeitpunkten aus intra- und interindividueller Perspektive. Als markanteste empirische Erkenntnis der Arbeit kann festgehalten werden, dass es durch das selbstgesteuert-konnektive Lernen mit E-Portfolio Blogs zu einer nachhaltigen Förderung der Medienkompetenz kommt, die sich auch in signifikanten Zusammenhängen mit den anderen Teildimensionen und intervenierenden Variablen widerspiegelt. Darüber hinaus bieten sich aber auch Potenziale für eine steigende Lernaktivität, einen ansteigenden Wissenserwerb und ein verbessertes Informations-/Wissensmanagement, die es aber noch weiterführend zu erforschen gilt. Demgegenüber können allerdings der entstehende und kontinuierlich hohe Aufwand sowie die erforderliche (Eigen-) Motivation als entscheidende Herausforderungen dieser Lernmethode identifiziert werden.

A Conceptual Model to Combine Creativity Techniques with Fuzzy Cognitive Maps for Enhanced Knowledge Management

This chapter introduces a conceptual model to combine creativity techniques with fuzzy cognitive maps (FCMs) and aims to support knowledge management methods by improving expert knowledge acquisition and aggregation. The aim of the conceptual model is to represent acquired knowledge in a manner that is as computer-understandable as possible with the intention of developing automated reasoning in the future as part of intelligent information systems. The formal represented knowledge thus may provide businesses with intelligent information integration. To this end, we introduce and evaluate various creativity techniques with a list of attributes to define the most suitable to combine with FCMs. This proposed combination enables enhanced knowledge management through the acquisition and representation of expert knowledge with FCMs. Our evaluation indicates that the creativity technique known as mind mapping is the most suitable technique in our set. Finally, a scenario from stakeholder management demonstrates the combination of mind mapping with FCMs as an integrated system.

Multi-Model Data Fusion to Improve an Early Warning System for Hypo-/Hyperglycemic Events

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

The Comal County Needs Assessment Youth Survey

A crucial link in preserving and protecting the future of our communities resides in maintaining the health and well being of our youth. While every member of the community owns an opinion regarding where to best utilize monies for prevention and intervention, the data to support such opinion is often scarce. In an effort to generate data-driven indices for community planning and action, the United Way of Comal County, Texas partnered with the University Of Texas - Houston Health Science Center, School Of Public Health to accomplish a county-specific needs assessment. A community-based participatory research emphasis utilizing the Mobilization for Action through Planning and Partnership (MAPP) format developed by the National Association of City and County Health Officials (NACCHO) was implemented to engage community members in identifying and addressing community priorities. The single greatest area of consensus and concern identified by community members was the health and well being of the youth population. Thus, a youth survey, targeting these specific areas of community concern, was designed, coordinated and administered to all 9-11th grade students in the county. 20% of the 3,698 completed surveys (72% response rate) were randomly selected for analysis. These 740 surveys were coded and scanned into an electronic survey database. Statistical analysis provided youth-reported data on the status of the multiple issues affecting the health and well being of the community's youth. These data will be reported back to the community stakeholders, as part of the larger Comal County Needs Assessment, for the purposes of community planning and action. Survey data will provide community planners with an awareness of the high risk behaviors and habit patterns amongst their youth. This knowledge will permit more effective targeting of the means for encouraging healthy behaviors and preventing the spread of disease. Further, the community-oriented, population-based nature of this effort will provide answers to questions raised by the community and will provide an effective launching pad for the development and implementation of targeted, preventive health strategies. ^

30 years of synoptic observations from Neumayer Station with links to datasets

The analysis of research data plays a key role in data-driven areas of science. Varieties of mixed research data sets exist and scientists aim to derive or validate hypotheses to find undiscovered knowledge. Many analysis techniques identify relations of an entire dataset only. This may level the characteristic behavior of different subgroups in the data. Like automatic subspace clustering, we aim at identifying interesting subgroups and attribute sets. We present a visual-interactive system that supports scientists to explore interesting relations between aggregated bins of multivariate attributes in mixed data sets. The abstraction of data to bins enables the application of statistical dependency tests as the measure of interestingness. An overview matrix view shows all attributes, ranked with respect to the interestingness of bins. Complementary, a node-link view reveals multivariate bin relations by positioning dependent bins close to each other. The system supports information drill-down based on both expert knowledge and algorithmic support. Finally, visual-interactive subset clustering assigns multivariate bin relations to groups. A list-based cluster result representation enables the scientist to communicate multivariate findings at a glance. We demonstrate the applicability of the system with two case studies from the earth observation domain and the prostate cancer research domain. In both cases, the system enabled us to identify the most interesting multivariate bin relations, to validate already published results, and, moreover, to discover unexpected relations.

Generating multimedia presentations that summarize the behavior of dynamic systems using a model-based approach

This article describes a knowledge-based method for generating multimedia descriptions that summarize the behavior of dynamic systems. We designed this method for users who monitor the behavior of a dynamic system with the help of sensor networks and make decisions according to prefixed management goals. Our method generates presentations using different modes such as text in natural language, 2D graphics and 3D animations. The method uses a qualitative representation of the dynamic system based on hierarchies of components and causal influences. The method includes an abstraction generator that uses the system representation to find and aggregate relevant data at an appropriate level of abstraction. In addition, the method includes a hierarchical planner to generate a presentation using a model with dis- course patterns. Our method provides an efficient and flexible solution to generate concise and adapted multimedia presentations that summarize thousands of time series. It is general to be adapted to differ- ent dynamic systems with acceptable knowledge acquisition effort by reusing and adapting intuitive rep- resentations. We validated our method and evaluated its practical utility by developing several models for an application that worked in continuous real time operation for more than 1 year, summarizing sen- sor data of a national hydrologic information system in Spain.

A Reuse-based Lightweight Method for Developing Linked Data Ontologies and Vocabularies

The uptake of Linked Data (LD) has promoted the proliferation of datasets and their associated ontologies for describing different domains. Par-ticular LD development characteristics such as agility and web-based architec-ture necessitate the revision, adaption, and lightening of existing methodologies for ontology development. This thesis proposes a lightweight method for ontol-ogy development in an LD context which will be based in data-driven agile de-velopments, existing resources to be reused, and the evaluation of the obtained products considering both classical ontological engineering principles and LD characteristics.

Nanoinformatics knowledge infrastructures: bringing efficient information management to nanomedical research

Nanotechnology represents an area of particular promise and significant opportunity across multiple scientific disciplines. Ongoing nanotechnology research ranges from the characterization of nanoparticles and nanomaterials to the analysis and processing of experimental data seeking correlations between nanoparticles and their functionalities and side effects. Due to their special properties, nanoparticles are suitable for cellular-level diagnostics and therapy, offering numerous applications in medicine, e.g. development of biomedical devices, tissue repair, drug delivery systems and biosensors. In nanomedicine, recent studies are producing large amounts of structural and property data, highlighting the role for computational approaches in information management. While in vitro and in vivo assays are expensive, the cost of computing is falling. Furthermore, improvements in the accuracy of computational methods (e.g. data mining, knowledge discovery, modeling and simulation) have enabled effective tools to automate the extraction, management and storage of these vast data volumes. Since this information is widely distributed, one major issue is how to locate and access data where it resides (which also poses data-sharing limitations). The novel discipline of nanoinformatics addresses the information challenges related to nanotechnology research. In this paper, we summarize the needs and challenges in the field and present an overview of extant initiatives and efforts.

Open Technologies for prototyping the Internet of Things

The worldwide "hyper-connection" of any object around us is the challenge that promises to cover the paradigm of the Internet of Things. If the Internet has colonized the daily life of more than 2000 million1 people around the globe, the Internet of Things faces of connecting more than 100000 million2 "things" by 2020. The underlying Internet of Things’ technologies are the cornerstone that promises to solve interrelated global problems such as exponential population growth, energy management in cities, and environmental sustainability in the average and long term. On the one hand, this Project has the goal of knowledge acquisition about prototyping technologies available in the market for the Internet of Things. On the other hand, the Project focuses on the development of a system for devices management within a Wireless Sensor and Actuator Network to offer some services accessible from the Internet. To accomplish the objectives, the Project will begin with a detailed analysis of various “open source” hardware platforms to encourage creative development of applications, and automatically extract information from the environment around them for transmission to external systems. In addition, web platforms that enable mass storage with the philosophy of the Internet of Things will be studied. The project will culminate in the proposal and specification of a service-oriented software architecture for embedded systems that allows communication between devices on the network, and the data transmission to external systems. Furthermore, it abstracts the complexities of hardware to application developers. RESUMEN. La “hiper-conexión” a nivel mundial de cualquier objeto que nos rodea es el desafío al que promete dar cobertura el paradigma de la Internet de las Cosas. Si la Internet ha colonizado el día a día de más de 2000 millones1 de personas en todo el planeta, la Internet de las Cosas plantea el reto de conectar a más de 100000 millones2 de “cosas” para el año 2020. Las tecnologías subyacentes de la Internet de las Cosas son la piedra angular que prometen dar solución a problemas globales interrelacionados como el crecimiento exponencial de la población, la gestión de la energía en las ciudades o la sostenibilidad del medioambiente a largo plazo. Este Proyecto Fin de Carrera tiene como principales objetivos por un lado, la adquisición de conocimientos acerca de las tecnologías para prototipos disponibles en el mercado para la Internet de las Cosas, y por otro lado el desarrollo de un sistema para la gestión de dispositivos de una red inalámbrica de sensores que ofrezcan unos servicios accesibles desde la Internet. Con el fin de abordar los objetivos marcados, el proyecto comenzará con un análisis detallado de varias plataformas hardware de tipo “open source” que estimulen el desarrollo creativo de aplicaciones y que permitan extraer de forma automática información del medio que les rodea para transmitirlo a sistemas externos para su posterior procesamiento. Por otro lado, se estudiarán plataformas web identificadas con la filosofía de la Internet de las Cosas que permitan el almacenamiento masivo de datos que diferentes plataformas hardware transfieren a través de la Internet. El Proyecto culminará con la propuesta y la especificación una arquitectura software orientada a servicios para sistemas empotrados que permita la comunicación entre los dispositivos de la red y la transmisión de datos a sistemas externos, así como facilitar el desarrollo de aplicaciones a los programadores mediante la abstracción de la complejidad del hardware.

The Role of Knowledge Modeling Techniques in Software Development: A General Approach Based on a Knowledge Management Tool

The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modeling. Then, the current state of knowledge modeling techniques is described where increased reliability is available through the modern knowledge acquisition techniques and supporting tools. The KSM (Knowledge Structure Manager) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are proposed about the feasibility of using the knowledge modeling tools and methods for general application design.

Terminological Importation for Adapting Reusable Knowledge Representation Components in the KSM Environment

This paper describes the adaptation approach of reusable knowledge representation components used in the KSM environment for the formulation and operationalisation of structured knowledge models. Reusable knowledge representation components in KSM are called primitives of representation. A primitive of representation provides: (1) a knowledge representation formalism (2) a set of tasks that use this knowledge together with several problem-solving methods to carry out these tasks (3) a knowledge acquisition module that provides different services to acquire and validate this knowledge (4) an abstract terminology about the linguistic categories included in the representation language associated to the primitive. Primitives of representation usually are domain independent. A primitive of representation can be adapted to support knowledge in a given domain by importing concepts from this domain. The paper describes how this activity can be carried out by mean of a terminological importation. Informally, a terminological importation partially populates an abstract terminology with concepts taken from a given domain. The information provided by the importation can be used by the acquisition and validation facilities to constraint the classes of knowledge that can be described using the representation formalism according to the domain knowledge. KSM provides the LINK-S language to specify terminological importation from a domain terminology to an abstract one. These terminologies are described in KSM by mean of the CONCEL language. Terminological importation is used to adapt reusable primitives of representation in order to increase the usability degree of such components in these domains. In addition, two primitives of representation can share a common vocabulary by importing common domain CONCEL terminologies (conceptual vocabularies). It is a necessary condition to make possible the interoperability between different, heterogeneous knowledge representation components in the framework of complex knowledge - based architectures.

LDP4j: a framework for the development of interoperable read-write linked data applications

Enterprises are increasingly using a wide range of heterogeneous information systems for executing and governing their business activities. Even if the adoption of service orientation has improved loose coupling and reusability, applications are still isolated data silos whose integration requires complex transformations and mediations. However, by leveraging Linked Data principles those data silos can now be seamlessly integrated, and this opens the door to new data-driven approaches for Enterprise Application Integration (EAI). In this paper we present LDP4j, an open souce Java-based framework for the development of interoperable read-write Linked Data applications, based on the W3C Linked Data Platform (LDP) specification.

Is the polarity of content producers strongly influenced by the results of the event?

This paper presents an approach to compare two types of data, subjective data (Polarity of Pan American Games 2011 event by country) and objective data (the number of medals won by each participating country), based on the Pearson corre- lation. When dealing with events described by people, knowledge acquisition is difficult because their structure is heterogeneous and subjective. A first step towards knowing the polarity of the information provided by people consists in automatically classifying the posts into clusters according to their polarity. The authors carried out a set of experiments using a corpus that consists of 5600 posts extracted from 168 Internet resources related to a specific event: the 2011 Pan American games. The approach is based on four components: a crawler, a filter, a synthesizer and a polarity analyzer. The PanAmerican approach automatically classifies the polarity of the event into clusters with the following results: 588 positive, 336 neutral, and 76 negative. Our work found out that the polarity of the content produced was strongly influenced by the results of the event with a correlation of .74. Thus, it is possible to conclude that the polarity of content is strongly affected by the results of the event. Finally, the accuracy of the PanAmerican approach is: .87, .90, and .80 according to the precision of the three classes of polarity evaluated.

Análisis de los factores de influencia en la adopción de herramientas colaborativas basadas en software social. Aplicación a entornos empresariales

En las últimas dos décadas, se ha puesto de relieve la importancia de los procesos de adquisición y difusión del conocimiento dentro de las empresas, y por consiguiente el estudio de estos procesos y la implementación de tecnologías que los faciliten ha sido un tema que ha despertado un creciente interés en la comunidad científica. Con el fin de facilitar y optimizar la adquisición y la difusión del conocimiento, las organizaciones jerárquicas han evolucionado hacia una configuración más plana, con estructuras en red que resulten más ágiles, disminuyendo la dependencia de una autoridad centralizada, y constituyendo organizaciones orientadas a trabajar en equipo. Al mismo tiempo, se ha producido un rápido desarrollo de las herramientas de colaboración Web 2.0, tales como blogs y wikis. Estas herramientas de colaboración se caracterizan por una importante componente social, y pueden alcanzar todo su potencial cuando se despliegan en las estructuras organizacionales planas. La Web 2.0 aparece como un concepto enfrentado al conjunto de tecnologías que existían a finales de los 90s basadas en sitios web, y se basa en la participación de los propios usuarios. Empresas del Fortune 500 –HP, IBM, Xerox, Cisco– las adoptan de inmediato, aunque no hay unanimidad sobre su utilidad real ni sobre cómo medirla. Esto se debe en parte a que no se entienden bien los factores que llevan a los empleados a adoptarlas, lo que ha llevado a fracasos en la implantación debido a la existencia de algunas barreras. Dada esta situación, y ante las ventajas teóricas que tienen estas herramientas de colaboración Web 2.0 para las empresas, los directivos de éstas y la comunidad científica muestran un interés creciente en conocer la respuesta a la pregunta: ¿cuáles son los factores que contribuyen a que los empleados de las empresas adopten estas herramientas Web 2.0 para colaborar? La respuesta a esta pregunta es compleja ya que se trata de herramientas relativamente nuevas en el contexto empresarial mediante las cuales se puede llevar a cabo la gestión del conocimiento en lugar del manejo de la información. El planteamiento que se ha llevado a cabo en este trabajo para dar respuesta a esta pregunta es la aplicación de los modelos de adopción tecnológica, que se basan en las percepciones de los individuos sobre diferentes aspectos relacionados con el uso de la tecnología. Bajo este enfoque, este trabajo tiene como objetivo principal el estudio de los factores que influyen en la adopción de blogs y wikis en empresas, mediante un modelo predictivo, teórico y unificado, de adopción tecnológica, con un planteamiento holístico a partir de la literatura de los modelos de adopción tecnológica y de las particularidades que presentan las herramientas bajo estudio y en el contexto especifico. Este modelo teórico permitirá determinar aquellos factores que predicen la intención de uso de las herramientas y el uso real de las mismas. El trabajo de investigación científica se estructura en cinco partes: introducción al tema de investigación, desarrollo del marco teórico, diseño del trabajo de investigación, análisis empírico, y elaboración de conclusiones. Desde el punto de vista de la estructura de la memoria de la tesis, las cinco partes mencionadas se desarrollan de forma secuencial a lo largo de siete capítulos, correspondiendo la primera parte al capítulo 1, la segunda a los capítulos 2 y 3, la tercera parte a los capítulos 4 y 5, la cuarta parte al capítulo 6, y la quinta y última parte al capítulo 7. El contenido del capítulo 1 se centra en el planteamiento del problema de investigación así como en los objetivos, principal y secundarios, que se pretenden cumplir a lo largo del trabajo. Así mismo, se expondrá el concepto de colaboración y su encaje con las herramientas colaborativas Web 2.0 que se plantean en la investigación y una introducción a los modelos de adopción tecnológica. A continuación se expone la justificación de la investigación, los objetivos de la misma y el plan de trabajo para su elaboración. Una vez introducido el tema de investigación, en el capítulo 2 se lleva a cabo una revisión de la evolución de los principales modelos de adopción tecnológica existentes (IDT, TRA, SCT, TPB, DTPB, C-TAM-TPB, UTAUT, UTAUT2), dando cuenta de sus fundamentos y factores empleados. Sobre la base de los modelos de adopción tecnológica expuestos en el capítulo 2, en el capítulo 3 se estudian los factores que se han expuesto en el capítulo 2 pero adaptados al contexto de las herramientas colaborativas Web 2.0. Con el fin de facilitar la comprensión del modelo final, los factores se agrupan en cuatro tipos: tecnológicos, de control, socio-normativos y otros específicos de las herramientas colaborativas. En el capítulo 4 se lleva a cabo la relación de los factores que son más apropiados para estudiar la adopción de las herramientas colaborativas y se define un modelo que especifica las relaciones entre los diferentes factores. Estas relaciones finalmente se convertirán en hipótesis de trabajo, y que habrá que contrastar mediante el estudio empírico. A lo largo del capítulo 5 se especifican las características del trabajo empírico que se lleva a cabo para contrastar las hipótesis que se habían enunciado en el capítulo 4. La naturaleza de la investigación es de carácter social, de tipo exploratorio, y se basa en un estudio empírico cuantitativo cuyo análisis se llevará a cabo mediante técnicas de análisis multivariante. En este capítulo se describe la construcción de las escalas del instrumento de medida, la metodología de recogida de datos, y posteriormente se presenta un análisis detallado de la población muestral, así como la comprobación de la existencia o no del sesgo atribuible al método de medida, lo que se denomina sesgo de método común (en inglés, Common Method Bias). El contenido del capítulo 6 corresponde al análisis de resultados, aunque previamente se expone la técnica estadística empleada, PLS-SEM, como herramienta de análisis multivariante con capacidad de análisis predictivo, así como la metodología empleada para validar el modelo de medida y el modelo estructural, los requisitos que debe cumplir la muestra, y los umbrales de los parámetros considerados. En la segunda parte del capítulo 6 se lleva a cabo el análisis empírico de los datos correspondientes a las dos muestras, una para blogs y otra para wikis, con el fin de validar las hipótesis de investigación planteadas en el capítulo 4. Finalmente, en el capítulo 7 se revisa el grado de cumplimiento de los objetivos planteados en el capítulo 1 y se presentan las contribuciones teóricas, metodológicas y prácticas derivadas del trabajo realizado. A continuación se exponen las conclusiones generales y detalladas por cada grupo de factores, así como las recomendaciones prácticas que se pueden extraer para orientar la implantación de estas herramientas en situaciones reales. Como parte final del capítulo se incluyen las limitaciones del estudio y se sugiere una serie de posibles líneas de trabajo futuras de interés, junto con los resultados de investigación parciales que se han obtenido durante el tiempo que ha durado la investigación. ABSTRACT In the last two decades, the relevance of knowledge acquisition and dissemination processes has been highlighted and consequently, the study of these processes and the implementation of the technologies that make them possible has generated growing interest in the scientific community. In order to ease and optimize knowledge acquisition and dissemination, hierarchical organizations have evolved to a more horizontal configuration with more agile net structures, decreasing the dependence of a centralized authority, and building team-working oriented organizations. At the same time, Web 2.0 collaboration tools such as blogs and wikis have quickly developed. These collaboration tools are characterized by a strong social component and can reach their full potential when they are deployed in horizontal organization structures. Web 2.0, based on user participation, arises as a concept to challenge the existing technologies of the 90’s which were based on websites. Fortune 500 companies – HP, IBM, Xerox, Cisco- adopted the concept immediately even though there was no unanimity about its real usefulness or how it could be measured. This is partly due to the fact that the factors that make the drivers for employees to adopt these tools are not properly understood, consequently leading to implementation failure due to the existence of certain barriers. Given this situation, and faced with theoretical advantages that these Web 2.0 collaboration tools seem to have for companies, managers and the scientific community are showing an increasing interest in answering the following question: Which factors contribute to the decision of the employees of a company to adopt the Web 2.0 tools for collaborative purposes? The answer is complex since these tools are relatively new in business environments. These tools allow us to move from an information Management approach to Knowledge Management. In order to answer this question, the chosen approach involves the application of technology adoption models, all of them based on the individual’s perception of the different aspects related to technology usage. From this perspective, this thesis’ main objective is to study the factors influencing the adoption of blogs and wikis in a company. This is done by using a unified and theoretical predictive model of technological adoption with a holistic approach that is based on literature of technological adoption models and the particularities that these tools presented under study and in a specific context. This theoretical model will allow us to determine the factors that predict the intended use of these tools and their real usage. The scientific research is structured in five parts: Introduction to the research subject, development of the theoretical framework, research work design, empirical analysis and drawing the final conclusions. This thesis develops the five aforementioned parts sequentially thorough seven chapters; part one (chapter one), part two (chapters two and three), part three (chapters four and five), parte four (chapters six) and finally part five (chapter seven). The first chapter is focused on the research problem statement and the objectives of the thesis, intended to be reached during the project. Likewise, the concept of collaboration and its link with the Web 2.0 collaborative tools is discussed as well as an introduction to the technology adoption models. Finally we explain the planning to carry out the research and get the proposed results. After introducing the research topic, the second chapter carries out a review of the evolution of the main existing technology adoption models (IDT, TRA, SCT, TPB, DTPB, C-TAM-TPB, UTAUT, UTAUT2), highlighting its foundations and factors used. Based on technology adoption models set out in chapter 2, the third chapter deals with the factors which have been discussed previously in chapter 2, but adapted to the context of Web 2.0 collaborative tools under study, blogs and wikis. In order to better understand the final model, the factors are grouped into four types: technological factors, control factors, social-normative factors and other specific factors related to the collaborative tools. The first part of chapter 4 covers the analysis of the factors which are more relevant to study the adoption of collaborative tools, and the second part proceeds with the theoretical model which specifies the relationship between the different factors taken into consideration. These relationships will become specific hypotheses that will be tested by the empirical study. Throughout chapter 5 we cover the characteristics of the empirical study used to test the research hypotheses which were set out in chapter 4. The nature of research is social, exploratory, and it is based on a quantitative empirical study whose analysis is carried out using multivariate analysis techniques. The second part of this chapter includes the description of the scales of the measuring instrument; the methodology for data gathering, the detailed analysis of the sample, and finally the existence of bias attributable to the measurement method, the "Bias Common Method" is checked. The first part of chapter 6 corresponds to the analysis of results. The statistical technique employed (PLS-SEM) is previously explained as a tool of multivariate analysis, capable of carrying out predictive analysis, and as the appropriate methodology used to validate the model in a two-stages analysis, the measurement model and the structural model. Futhermore, it is necessary to check the requirements to be met by the sample and the thresholds of the parameters taken into account. In the second part of chapter 6 an empirical analysis of the data is performed for the two samples, one for blogs and the other for wikis, in order to validate the research hypothesis proposed in chapter 4. Finally, in chapter 7 the fulfillment level of the objectives raised in chapter 1 is reviewed and the theoretical, methodological and practical conclusions derived from the results of the study are presented. Next, we cover the general conclusions, detailing for each group of factors including practical recommendations that can be drawn to guide implementation of these tools in real situations in companies. As a final part of the chapter the limitations of the study are included and a number of potential future researches suggested, along with research partial results which have been obtained thorough the research.