877 resultados para User acceptance


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Identification and tracking of objects in specific environments such as harbors or security areas is a matter of great importance nowadays. With this purpose, numerous systems based on different technologies have been developed, resulting in a great amount of gathered data displayed through a variety of interfaces. Such amount of information has to be evaluated by human operators in order to take the correct decisions, sometimes under highly critical situations demanding both speed and accuracy. In order to face this problem we describe IDT-3D, a platform for identification and tracking of vessels in a harbour environment able to represent fused information in real time using a Virtual Reality application. The effectiveness of using IDT-3D as an integrated surveillance system is currently under evaluation. Preliminary results point to a significant decrease in the times of reaction and decision making of operators facing up a critical situation. Although the current application focus of IDT-3D is quite specific, the results of this research could be extended to the identification and tracking of targets in other controlled environments of interest as coastlines, borders or even urban areas.

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Improving patient self-management can have a greater impact than improving any clinical treatment (WHO). We propose here a systematic and comprehensive user centered design approach for delivering a technological platform for diabetes disease management. The system was developed under the METABO research project framework, involving patients from 3 different clinical centers in Parma, Modena and Madrid.

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We present an evaluation of a spoken language dialogue system with a module for the management of userrelated information, stored as user preferences and privileges. The flexibility of our dialogue management approach, based on Bayesian Networks (BN), together with a contextual information module, which performs different strategies for handling such information, allows us to include user information as a new level into the Context Manager hierarchy. We propose a set of objective and subjective metrics to measure the relevance of the different contextual information sources. The analysis of our evaluation scenarios shows that the relevance of the short-term information (i.e. the system status) remains pretty stable throughout the dialogue, whereas the dialogue history and the user profile (i.e. the middle-term and the long-term information, respectively) play a complementary role, evolving their usefulness as the dialogue evolves.

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This paper describes a novel architecture to introduce automatic annotation and processing of semantic sensor data within context-aware applications. Based on the well-known state-charts technologies, and represented using W3C SCXML language combined with Semantic Web technologies, our architecture is able to provide enriched higher-level semantic representations of user’s context. This capability to detect and model relevant user situations allows a seamless modeling of the actual interaction situation, which can be integrated during the design of multimodal user interfaces (also based on SCXML) for them to be adequately adapted. Therefore, the final result of this contribution can be described as a flexible context-aware SCXML-based architecture, suitable for both designing a wide range of multimodal context-aware user interfaces, and implementing the automatic enrichment of sensor data, making it available to the entire Semantic Sensor Web

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Advances in solid-state lighting have overcome common limitations on optical wireless such as power needs due to light dispersion. It's been recently proposed the modification of lamp's drivers to take advantages of its switching behaviour to include data links maintaining the illumination control they provide. In this paper, a remote access application using visible light communications is presented that provides wireless access to a remote computer using a touchscreen as user interface

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This paper describes the participation of DAEDALUS at the LogCLEF lab in CLEF 2011. This year, the objectives of our participation are twofold. The first topic is to analyze if there is any measurable effect on the success of the search queries if the native language and the interface language chosen by the user are different. The idea is to determine if this difference may condition the way in which the user interacts with the search application. The second topic is to analyze the user context and his/her interaction with the system in the case of successful queries, to discover out any relation among the user native language, the language of the resource involved and the interaction strategy adopted by the user to find out such resource. Only 6.89% of queries are successful out of the 628,607 queries in the 320,001 sessions with at least one search query in the log. The main conclusion that can be drawn is that, in general for all languages, whether the native language matches the interface language or not does not seem to affect the success rate of the search queries. On the other hand, the analysis of the strategy adopted by users when looking for a particular resource shows that people tend to use the simple search tool, frequently first running short queries build up of just one specific term and then browsing through the results to locate the expected resource

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The increasing demand of security oriented to mobile applications has raised the attention to biometrics, as a proper and suitable solution for providing secure environment to mobile devices. With this aim, this document presents a biometric system based on hand geometry oriented to mobile devices, involving a high degree of freedom in terms of illumination, hand rotation and distance to camera. The user takes a picture of their own hand in the free space, without requiring any flat surface to locate the hand, and without removals of rings, bracelets or watches. The proposed biometric system relies on an accurate segmentation procedure, able to isolate hands from any background; a feature extraction, invariant to orientation, illumination, distance to camera and background; and a user classification, based on k-Nearest Neighbor approach, able to provide an accurate results on individual identification. The proposed method has been evaluated with two own databases collected with a HTC mobile. First database contains 120 individuals, with 20 acquisitions of both hands. Second database is a synthetic database, containing 408000 images of hand samples in different backgrounds: tiles, grass, water, sand, soil and the like. The system is able to identify individuals properly with False Reject Rate of 5.78% and False Acceptance Rate of 0.089%, using 60 features (15 features per finger)

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Biometrics applied to mobile devices are of great interest for security applications. Daily scenarios can benefit of a combination of both the most secure systems and most simple and extended devices. This document presents a hand biometric system oriented to mobile devices, proposing a non-intrusive, contact-less acquisition process where final users should take a picture of their hand in free-space with a mobile device without removals of rings, bracelets or watches. The main contribution of this paper is threefold: firstly, a feature extraction method is proposed, providing invariant hand measurements to previous changes; second contribution consists of providing a template creation based on hand geometric distances, requiring information from only one individual, without considering data from the rest of individuals within the database; finally, a proposal for template matching is proposed, minimizing the intra-class similarity and maximizing the inter-class likeliness. The proposed method is evaluated using three publicly available contact-less, platform-free databases. In addition, the results obtained with these databases will be compared to the results provided by two competitive pattern recognition techniques, namely Support Vector Machines (SVM) and k-Nearest Neighbour, often employed within the literature. Therefore, this approach provides an appropriate solution to adapt hand biometrics to mobile devices, with an accurate results and a non-intrusive acquisition procedure which increases the overall acceptance from the final user.

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When mapping is formulated in a Bayesian framework, the need of specifying a prior for the environment arises naturally. However, so far, the use of a particular structure prior has been coupled to working with a particular representation. We describe a system that supports inference with multiple priors while keeping the same dense representation. The priors are rigorously described by the user in a domain-specific language. Even though we work very close to the measurement space, we are able to represent structure constraints with the same expressivity as methods based on geometric primitives. This approach allows the intrinsic degrees of freedom of the environment’s shape to be recovered. Experiments with simulated and real data sets will be presented

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Abstract Web 2.0 applications enabled users to classify information resources using their own vocabularies. The bottom-up nature of these user-generated classification systems have turned them into interesting knowledge sources, since they provide a rich terminology generated by potentially large user communities. Previous research has shown that it is possible to elicit some emergent semantics from the aggregation of individual classifications in these systems. However the generation of ontologies from them is still an open research problem. In this thesis we address the problem of how to tap into user-generated classification systems for building domain ontologies. Our objective is to design a method to develop domain ontologies from user-generated classifications systems. To do so, we rely on ontologies in the Web of Data to formalize the semantics of the knowledge collected from the classification system. Current ontology development methodologies have recognized the importance of reusing knowledge from existing resources. Thus, our work is framed within the NeOn methodology scenario for building ontologies by reusing and reengineering non-ontological resources. The main contributions of this work are: An integrated method to develop ontologies from user-generated classification systems. With this method we extract a domain terminology from the classification system and then we formalize the semantics of this terminology by reusing ontologies in the Web of Data. Identification and adaptation of existing techniques for implementing the activities in the method so that they can fulfill the requirements of each activity. A novel study about emerging semantics in user-generated lists. Resumen La web 2.0 permitió a los usuarios clasificar recursos de información usando su propio vocabulario. Estos sistemas de clasificación generados por usuarios son recursos interesantes para la extracción de conocimiento debido principalmente a que proveen una extensa terminología generada por grandes comunidades de usuarios. Se ha demostrado en investigaciones previas que es posible obtener una semántica emergente de estos sistemas. Sin embargo la generación de ontologías a partir de ellos es todavía un problema de investigación abierto. Esta tesis trata el problema de cómo aprovechar los sistemas de clasificación generados por usuarios en la construcción de ontologías de dominio. Así el objetivo de la tesis es diseñar un método para desarrollar ontologías de dominio a partir de sistemas de clasificación generados por usuarios. El método propuesto reutiliza conceptualizaciones existentes en ontologías publicadas en la Web de Datos para formalizar la semántica del conocimiento que se extrae del sistema de clasificación. Por tanto, este trabajo está enmarcado dentro del escenario para desarrollar ontologías mediante la reutilización y reingeniería de recursos no ontológicos que se ha definido en la Metodología NeOn. Las principales contribuciones de este trabajo son: Un método integrado para desarrollar una ontología de dominio a partir de sistemas de clasificación generados por usuarios. En este método se extrae una terminología de dominio del sistema de clasificación y posteriormente se formaliza su semántica reutilizando ontologías en la Web de Datos. La identificación y adaptación de un conjunto de técnicas para implementar las actividades propuestas en el método de tal manera que puedan cumplir automáticamente los requerimientos de cada actividad. Un novedoso estudio acerca de la semántica emergente en las listas generadas por usuarios en la Web.

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We present a static analysis that infers both upper and lower bounds on the usage that a logic program makes of a set of user-definable resources. The inferred bounds will in general be functions of input data sizes. A resource in our approach is a quite general, user-defined notion which associates a basic cost function with elementary operations. The analysis then derives the related (upper- and lower-bound) resource usage functions for all predicates in the program. We also present an assertion language which is used to define both such resources and resourcerelated properties that the system can then check based on the results of the analysis. We have performed some preliminary experiments with some concrete resources such as execution steps, bytes sent or received by an application, number of files left open, number of accesses to a datábase, number of calis to a procedure, number of asserts/retracts, etc. Applications of our analysis include resource consumption verification and debugging (including for mobile code), resource control in parallel/distributed computing, and resource-oriented specialization.

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Automatic cost analysis of programs has been traditionally concentrated on a reduced number of resources such as execution steps, time, or memory. However, the increasing relevance of analysis applications such as static debugging and/or certiflcation of user-level properties (including for mobile code) makes it interesting to develop analyses for resource notions that are actually application-dependent. This may include, for example, bytes sent or received by an application, number of files left open, number of SMSs sent or received, number of accesses to a datábase, money spent, energy consumption, etc. We present a fully automated analysis for inferring upper bounds on the usage that a Java bytecode program makes of a set of application programmer-deflnable resources. In our context, a resource is defined by programmer-provided annotations which state the basic consumption that certain program elements make of that resource. From these deflnitions our analysis derives functions which return an upper bound on the usage that the whole program (and individual blocks) make of that resource for any given set of input data sizes. The analysis proposed is independent of the particular resource. We also present some experimental results from a prototype implementation of the approach covering a signiflcant set of interesting resources.

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Abstract is not available.

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Las Tecnologías de la Información y la Comunicación en general e Internet en particular han supuesto una revolución en nuestra forma de comunicarnos, relacionarnos, producir, comprar y vender acortando tiempo y distancias entre proveedores y consumidores. A la paulatina penetración del ordenador, los teléfonos inteligentes y la banda ancha fija y/o móvil ha seguido un mayor uso de estas tecnologías entre ciudadanos y empresas. El comercio electrónico empresa–consumidor (B2C) alcanzó en 2010 en España un volumen de 9.114 millones de euros, con un incremento del 17,4% respecto al dato registrado en 2009. Este crecimiento se ha producido por distintos hechos: un incremento en el porcentaje de internautas hasta el 65,1% en 2010 de los cuales han adquirido productos o servicios a través de la Red un 43,1% –1,6 puntos porcentuales más respecto a 2010–. Por otra parte, el gasto medio por comprador ha ascendido a 831€ en 2010, lo que supone un incremento del 10,9% respecto al año anterior. Si segmentamos a los compradores según por su experiencia anterior de compra podemos encontrar dos categorías: el comprador novel –que adquirió por primera vez productos o servicios en 2010– y el comprador constante –aquel que había adquirido productos o servicios en 2010 y al menos una vez en años anteriores–. El 85,8% de los compradores se pueden considerar como compradores constantes: habían comprado en la Red en 2010, pero también lo habían hecho anteriormente. El comprador novel tiene un perfil sociodemográfico de persona joven de entre 15–24 años, con estudios secundarios, de clase social media y media–baja, estudiante no universitario, residente en poblaciones pequeñas y sigue utilizando fórmulas de pago como el contra–reembolso (23,9%). Su gasto medio anual ascendió en 2010 a 449€. El comprador constante, o comprador que ya había comprado en Internet anteriormente, tiene un perfil demográfico distinto: estudios superiores, clase alta, trabajador y residente en grandes ciudades, con un comportamiento maduro en la compra electrónica dada su mayor experiencia –utiliza con mayor intensidad canales exclusivos en Internet que no disponen de tienda presencial–. Su gasto medio duplica al observado en compradores noveles (con una media de 930€ anuales). Por tanto, los compradores constantes suponen una mayoría de los compradores con un gasto medio que dobla al comprador que ha adoptado el medio recientemente. Por consiguiente es de interés estudiar los factores que predicen que un internauta vuelva a adquirir un producto o servicio en la Red. La respuesta a esta pregunta no se ha revelado sencilla. En España, la mayoría de productos y servicios aún se adquieren de manera presencial, con una baja incidencia de las ventas a distancia como la teletienda, la venta por catálogo o la venta a través de Internet. Para dar respuesta a las preguntas planteadas se ha investigado desde distintos puntos de vista: se comenzará con un estudio descriptivo desde el punto de vista de la demanda que trata de caracterizar la situación del comercio electrónico B2C en España, poniendo el foco en las diferencias entre los compradores constantes y los nuevos compradores. Posteriormente, la investigación de modelos de adopción y continuidad en el uso de las tecnologías y de los factores que inciden en dicha continuidad –con especial interés en el comercio electrónico B2C–, permiten afrontar el problema desde la perspectiva de las ecuaciones estructurales pudiendo también extraer conclusiones de tipo práctico. Este trabajo sigue una estructura clásica de investigación científica: en el capítulo 1 se introduce el tema de investigación, continuando con una descripción del estado de situación del comercio electrónico B2C en España utilizando fuentes oficiales (capítulo 2). Posteriormente se desarrolla el marco teórico y el estado del arte de modelos de adopción y de utilización de las tecnologías (capítulo 3) y de los factores principales que inciden en la adopción y continuidad en el uso de las tecnologías (capítulo 4). El capítulo 5 desarrolla las hipótesis de la investigación y plantea los modelos teóricos. Las técnicas estadísticas a utilizar se describen en el capítulo 6, donde también se analizan los resultados empíricos sobre los modelos desarrollados en el capítulo 5. El capítulo 7 expone las principales conclusiones de la investigación, sus limitaciones y propone nuevas líneas de investigación. La primera parte corresponde al capítulo 1, que introduce la investigación justificándola desde un punto de vista teórico y práctico. También se realiza una breve introducción a la teoría del comportamiento del consumidor desde una perspectiva clásica. Se presentan los principales modelos de adopción y se introducen los modelos de continuidad de utilización que se estudiarán más detalladamente en el capítulo 3. En este capítulo se desarrollan los objetivos principales y los objetivos secundarios, se propone el mapa mental de la investigación y se planifican en un cronograma los principales hitos del trabajo. La segunda parte corresponde a los capítulos dos, tres y cuatro. En el capítulo 2 se describe el comercio electrónico B2C en España utilizando fuentes secundarias. Se aborda un diagnóstico del sector de comercio electrónico y su estado de madurez en España. Posteriormente, se analizan las diferencias entre los compradores constantes, principal interés de este trabajo, frente a los compradores noveles, destacando las diferencias de perfiles y usos. Para los dos segmentos se estudian aspectos como el lugar de acceso a la compra, la frecuencia de compra, los medios de pago utilizados o las actitudes hacia la compra. El capítulo 3 comienza desarrollando los principales conceptos sobre la teoría del comportamiento del consumidor, para continuar estudiando los principales modelos de adopción de tecnología existentes, analizando con especial atención su aplicación en comercio electrónico. Posteriormente se analizan los modelos de continuidad en el uso de tecnologías (Teoría de la Confirmación de Expectativas; Teoría de la Justicia), con especial atención de nuevo a su aplicación en el comercio electrónico. Una vez estudiados los principales modelos de adopción y continuidad en el uso de tecnologías, el capítulo 4 analiza los principales factores que se utilizan en los modelos: calidad, valor, factores basados en la confirmación de expectativas –satisfacción, utilidad percibida– y factores específicos en situaciones especiales –por ejemplo, tras una queja– como pueden ser la justicia, las emociones o la confianza. La tercera parte –que corresponde al capítulo 5– desarrolla el diseño de la investigación y la selección muestral de los modelos. En la primera parte del capítulo se enuncian las hipótesis –que van desde lo general a lo particular, utilizando los factores específicos analizados en el capítulo 4– para su posterior estudio y validación en el capítulo 6 utilizando las técnicas estadísticas apropiadas. A partir de las hipótesis, y de los modelos y factores estudiados en los capítulos 3 y 4, se definen y vertebran dos modelos teóricos originales que den respuesta a los retos de investigación planteados en el capítulo 1. En la segunda parte del capítulo se diseña el trabajo empírico de investigación definiendo los siguientes aspectos: alcance geográfico–temporal, tipología de la investigación, carácter y ambiente de la investigación, fuentes primarias y secundarias utilizadas, técnicas de recolección de datos, instrumentos de medida utilizados y características de la muestra utilizada. Los resultados del trabajo de investigación constituyen la cuarta parte de la investigación y se desarrollan en el capítulo 6, que comienza analizando las técnicas estadísticas basadas en Modelos de Ecuaciones Estructurales. Se plantean dos alternativas, modelos confirmatorios correspondientes a Métodos Basados en Covarianzas (MBC) y modelos predictivos. De forma razonada se eligen las técnicas predictivas dada la naturaleza exploratoria de la investigación planteada. La segunda parte del capítulo 6 desarrolla el análisis de los resultados de los modelos de medida y modelos estructurales construidos con indicadores formativos y reflectivos y definidos en el capítulo 4. Para ello se validan, sucesivamente, los modelos de medida y los modelos estructurales teniendo en cuenta los valores umbrales de los parámetros estadísticos necesarios para la validación. La quinta parte corresponde al capítulo 7, que desarrolla las conclusiones basándose en los resultados del capítulo 6, analizando los resultados desde el punto de vista de las aportaciones teóricas y prácticas, obteniendo conclusiones para la gestión de las empresas. A continuación, se describen las limitaciones de la investigación y se proponen nuevas líneas de estudio sobre distintos temas que han ido surgiendo a lo largo del trabajo. Finalmente, la bibliografía recoge todas las referencias utilizadas a lo largo de este trabajo. Palabras clave: comprador constante, modelos de continuidad de uso, continuidad en el uso de tecnologías, comercio electrónico, B2C, adopción de tecnologías, modelos de adopción tecnológica, TAM, TPB, IDT, UTAUT, ECT, intención de continuidad, satisfacción, confianza percibida, justicia, emociones, confirmación de expectativas, calidad, valor, PLS. ABSTRACT Information and Communication Technologies in general, but more specifically those related to the Internet in particular, have changed the way in which we communicate, relate to one another, produce, and buy and sell products, reducing the time and shortening the distance between suppliers and consumers. The steady breakthrough of computers, Smartphones and landline and/or wireless broadband has been greatly reflected in its large scale use by both individuals and businesses. Business–to–consumer (B2C) e–commerce reached a volume of 9,114 million Euros in Spain in 2010, representing a 17.4% increase with respect to the figure in 2009. This growth is due in part to two different facts: an increase in the percentage of web users to 65.1% en 2010, 43.1% of whom have acquired products or services through the Internet– which constitutes 1.6 percentage points higher than 2010. On the other hand, the average spending by individual buyers rose to 831€ en 2010, constituting a 10.9% increase with respect to the previous year. If we select buyers according to whether or not they have previously made some type of purchase, we can divide them into two categories: the novice buyer–who first made online purchases in 2010– and the experienced buyer: who also made purchases in 2010, but had done so previously as well. The socio–demographic profile of the novice buyer is that of a young person between 15–24 years of age, with secondary studies, middle to lower–middle class, and a non–university educated student who resides in smaller towns and continues to use payment methods such as cash on delivery (23.9%). In 2010, their average purchase grew to 449€. The more experienced buyer, or someone who has previously made purchases online, has a different demographic profile: highly educated, upper class, resident and worker in larger cities, who exercises a mature behavior when making online purchases due to their experience– this type of buyer frequently uses exclusive channels on the Internet that don’t have an actual store. His or her average purchase doubles that of the novice buyer (with an average purchase of 930€ annually.) That said, the experienced buyers constitute the majority of buyers with an average purchase that doubles that of novice buyers. It is therefore of interest to study the factors that help to predict whether or not a web user will buy another product or use another service on the Internet. The answer to this question has proven not to be so simple. In Spain, the majority of goods and services are still bought in person, with a low amount of purchases being made through means such as the Home Shopping Network, through catalogues or Internet sales. To answer the questions that have been posed here, an investigation has been conducted which takes into consideration various viewpoints: it will begin with a descriptive study from the perspective of the supply and demand that characterizes the B2C e–commerce situation in Spain, focusing on the differences between experienced buyers and novice buyers. Subsequently, there will be an investigation concerning the technology acceptance and continuity of use of models as well as the factors that have an effect on their continuity of use –with a special focus on B2C electronic commerce–, which allows for a theoretic approach to the problem from the perspective of the structural equations being able to reach practical conclusions. This investigation follows the classic structure for a scientific investigation: the subject of the investigation is introduced (Chapter 1), then the state of the B2C e–commerce in Spain is described citing official sources of information (Chapter 2), the theoretical framework and state of the art of technology acceptance and continuity models are developed further (Chapter 3) and the main factors that affect their acceptance and continuity (Chapter 4). Chapter 5 explains the hypothesis behind the investigation and poses the theoretical models that will be confirmed or rejected partially or completely. In Chapter 6, the technical statistics that will be used are described briefly as well as an analysis of the empirical results of the models put forth in Chapter 5. Chapter 7 explains the main conclusions of the investigation, its limitations and proposes new projects. First part of the project, chapter 1, introduces the investigation, justifying it from a theoretical and practical point of view. It is also a brief introduction to the theory of consumer behavior from a standard perspective. Technology acceptance models are presented and then continuity and repurchase models are introduced, which are studied more in depth in Chapter 3. In this chapter, both the main and the secondary objectives are developed through a mind map and a timetable which highlights the milestones of the project. The second part of the project corresponds to Chapters Two, Three and Four. Chapter 2 describes the B2C e–commerce in Spain from the perspective of its demand, citing secondary official sources. A diagnosis concerning the e–commerce sector and the status of its maturity in Spain is taken on, as well as the barriers and alternative methods of e–commerce. Subsequently, the differences between experienced buyers, which are of particular interest to this project, and novice buyers are analyzed, highlighting the differences between their profiles and their main transactions. In order to study both groups, aspects such as the place of purchase, frequency with which online purchases are made, payment methods used and the attitudes of the purchasers concerning making online purchases are taken into consideration. Chapter 3 begins by developing the main concepts concerning consumer behavior theory in order to continue the study of the main existing acceptance models (among others, TPB, TAM, IDT, UTAUT and other models derived from them) – paying special attention to their application in e–commerce–. Subsequently, the models of technology reuse are analyzed (CDT, ECT; Theory of Justice), focusing again specifically on their application in e–commerce. Once the main technology acceptance and reuse models have been studied, Chapter 4 analyzes the main factors that are used in these models: quality, value, factors based on the contradiction of expectations/failure to meet expectations– satisfaction, perceived usefulness– and specific factors pertaining to special situations– for example, after receiving a complaint justice, emotions or confidence. The third part– which appears in Chapter 5– develops the plan for the investigation and the sample selection for the models that have been designed. In the first section of the Chapter, the hypothesis is presented– beginning with general ideas and then becoming more specific, using the detailed factors that were analyzed in Chapter 4– for its later study and validation in Chapter 6– as well as the corresponding statistical factors. Based on the hypothesis and the models and factors that were studied in Chapters 3 and 4, two original theoretical models are defined and organized in order to answer the questions posed in Chapter 1. In the second part of the Chapter, the empirical investigation is designed, defining the following aspects: geographic–temporal scope, type of investigation, nature and setting of the investigation, primary and secondary sources used, data gathering methods, instruments according to the extent of their use and characteristics of the sample used. The results of the project constitute the fourth part of the investigation and are developed in Chapter 6, which begins analyzing the statistical techniques that are based on the Models of Structural Equations. Two alternatives are put forth: confirmatory models which correspond to Methods Based on Covariance (MBC) and predictive models– Methods Based on Components–. In a well–reasoned manner, the predictive techniques are chosen given the explorative nature of the investigation. The second part of Chapter 6 explains the results of the analysis of the measurement models and structural models built by the formative and reflective indicators defined in Chapter 4. In order to do so, the measurement models and the structural models are validated one by one, while keeping in mind the threshold values of the necessary statistic parameters for their validation. The fifth part corresponds to Chapter 7 which explains the conclusions of the study, basing them on the results found in Chapter 6 and analyzing them from the perspective of the theoretical and practical contributions, and consequently obtaining conclusions for business management. The limitations of the investigation are then described and new research lines about various topics that came up during the project are proposed. Lastly, all of the references that were used during the project are listed in a final bibliography. Key Words: constant buyer, repurchase models, continuity of use of technology, e–commerce, B2C, technology acceptance, technology acceptance models, TAM, TPB, IDT, UTAUT, ECT, intention of repurchase, satisfaction, perceived trust/confidence, justice, feelings, the contradiction of expectations, quality, value, PLS.

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The new user cold start issue represents a serious problem in recommender systems as it can lead to the loss of new users who decide to stop using the system due to the lack of accuracy in the recommenda- tions received in that first stage in which they have not yet cast a significant number of votes with which to feed the recommender system?s collaborative filtering core. For this reason it is particularly important to design new similarity metrics which provide greater precision in the results offered to users who have cast few votes. This paper presents a new similarity measure perfected using optimization based on neu- ral learning, which exceeds the best results obtained with current metrics. The metric has been tested on the Netflix and Movielens databases, obtaining important improvements in the measures of accuracy, precision and recall when applied to new user cold start situations. The paper includes the mathematical formalization describing how to obtain the main quality measures of a recommender system using leave- one-out cross validation.