ARE USERS THE NEXT ENTREPRENEURS? A CASE STUDY ON THE VIDEO GAME INDUSTRY.

Knowledge based-entrepreneurial firms struggle to survive because they must be simultaneously entrepreneurial on several dimensions. Can those firms rely on users to achieve sufficient efficiency in some entrepreneurial dimensions? To answer this question we drew on the entrepreneurial theories of the firm and on the users/innovator literature. In this work we present the plural entrepreneurship framework and then with a longitudinal case study of a mobile phone video-game firm which relies on users to improve their games we show that the user can significantly enhance the efficiency of the innovation of the firm. We also show that the other important dimensions of the firm behavior (organization, business model) can be significantly improved by the implication of users.Plural entrepreneurship; management of innovation; Video-game case study.

A matter of time: phases of customer co-creation community participation and their impact on customer behavior

Despite the growing relevance of co-creating customer communities only little scientific evidence is available on their impact on transactional behavior of participants. Previous research has mostly used self-reported data or distinguished only between during and pre-community phases obtaining mixed results. However, the author proposes that co-creating community activity takes place in five distinguishable phases and changes in transactional behavior are limited to certain phases. Using 33 months of transactional data of a Dutch online auction provider a study was conducted covering all five phases of the community co-creation process from community planning over community set-up, co-development and co-testing to post-launch. The overall results indicate mixed effects of community participation on the different transactional variables during the co-creation process. Community participation had positive effects on auctions listing behavior at the community set-up, co-development and post-launch phases, whereby the number of auctions listed peaked during the community set-up phase. These results suggest that the impact on transactional behavior differs between co-creation phases and different psychological mechanism limited to certain phases might trigger the respective changes.NSBE - UN

EcoGIS – GIS tools for ecosystem approaches to fisheries management

Executive Summary: The EcoGIS project was launched in September 2004 to investigate how Geographic Information Systems (GIS), marine data, and custom analysis tools can better enable fisheries scientists and managers to adopt Ecosystem Approaches to Fisheries Management (EAFM). EcoGIS is a collaborative effort between NOAA’s National Ocean Service (NOS) and National Marine Fisheries Service (NMFS), and four regional Fishery Management Councils. The project has focused on four priority areas: Fishing Catch and Effort Analysis, Area Characterization, Bycatch Analysis, and Habitat Interactions. Of these four functional areas, the project team first focused on developing a working prototype for catch and effort analysis: the Fishery Mapper Tool. This ArcGIS extension creates time-and-area summarized maps of fishing catch and effort from logbook, observer, or fishery-independent survey data sets. Source data may come from Oracle, Microsoft Access, or other file formats. Feedback from beta-testers of the Fishery Mapper was used to debug the prototype, enhance performance, and add features. This report describes the four priority functional areas, the development of the Fishery Mapper tool, and several themes that emerged through the parallel evolution of the EcoGIS project, the concept and implementation of the broader field of Ecosystem Approaches to Management (EAM), data management practices, and other EAM toolsets. In addition, a set of six succinct recommendations are proposed on page 29. One major conclusion from this work is that there is no single “super-tool” to enable Ecosystem Approaches to Management; as such, tools should be developed for specific purposes with attention given to interoperability and automation. Future work should be coordinated with other GIS development projects in order to provide “value added” and minimize duplication of efforts. In addition to custom tools, the development of cross-cutting Regional Ecosystem Spatial Databases will enable access to quality data to support the analyses required by EAM. GIS tools will be useful in developing Integrated Ecosystem Assessments (IEAs) and providing pre- and post-processing capabilities for spatially-explicit ecosystem models. Continued funding will enable the EcoGIS project to develop GIS tools that are immediately applicable to today’s needs. These tools will enable simplified and efficient data query, the ability to visualize data over time, and ways to synthesize multidimensional data from diverse sources. These capabilities will provide new information for analyzing issues from an ecosystem perspective, which will ultimately result in better understanding of fisheries and better support for decision-making. (PDF file contains 45 pages.

What Causes My Test Alarm? Automatic Cause Analysis for Test Alarms in System and Integration Testing

Driven by new software development processes and testing in clouds, system and integration testing nowadays tends to produce enormous number of alarms. Such test alarms lay an almost unbearable burden on software testing engineers who have to manually analyze the causes of these alarms. The causes are critical because they decide which stakeholders are responsible to fix the bugs detected during the testing. In this paper, we present a novel approach that aims to relieve the burden by automating the procedure. Our approach, called Cause Analysis Model, exploits information retrieval techniques to efficiently infer test alarm causes based on test logs. We have developed a prototype and evaluated our tool on two industrial datasets with more than 14,000 test alarms. Experiments on the two datasets show that our tool achieves an accuracy of 58.3% and 65.8%, respectively, which outperforms the baseline algorithms by up to 13.3%. Our algorithm is also extremely efficient, spending about 0.1s per cause analysis. Due to the attractive experimental results, our industrial partner, a leading information and communication technology company in the world, has deployed the tool and it achieves an average accuracy of 72% after two months of running, nearly three times more accurate than a previous strategy based on regular expressions.Comment: 12 page

Failure factors of technological driven start-ups: datris solutions case study

Dissertação de mestrado em International BusinessThis internship report reflects the status and evolution of the technological driven start-up, Datris Solutions, which is a start-up focused on exploring opportunities in the open data and membership management applications sectors. Datris was created in 2015 and presently, in 2018 has yet to release a finished product that can be used to generate revenue. Continuous issues afflict the development of the start-up’s team and products which resulted in the slow progress and evolution of the two. In an attempt to pump fresh ideas and motivation into the current start-up’s team members, additional personal was hired, in this case a marketing research intern to assist the team in every marketing related effort with special focus for marketing research. This created the adequate scenery for an internship in the area of International Business since it allowed a look into the development and evolution of a young technological driven startup in a foreign country. The knowledge gained during the regular theoretical modules of the International Business masters classes provided the necessary tools to assess an international business/start-up health and the insight to provide advice on what would be the best suggestions to increase the start-up’s productivity, development and how to develop an accurate market research. With that in mind, this internship report will focus on assessing the current factors that are inhibiting the development and growth potential of technological driven start-ups. By identifying, analysing and comparing them to the literature research findings regarding failure factors that inhibit technological start-up development, we hope to contribute to the current literature. In addition, we will suggest an action plan to reduce the influence of these negative factors to ensure a better survivability rate for the start-up for the years to come.Este relatório de estágio reflete o status e a evolução da start-up tecnologicamente orientada, Datris Solutions, que é uma start-up focada na exploração de oportunidades nos setores de aplicativos abertos de gerenciamento de dados e de membros. A Datris foi criada em 2015 e atualmente, em 2018, ainda não lançou um produto acabado que pode ser usado para gerar receita. Problemas contínuos afligem o desenvolvimento da equipa e dos produtos da startup, que resultaram no lento progresso e evolução dos dois. Na tentativa de impulsionar novas ideias e motivação para os atuais membros da equipa da start-up, foi contratado um membro adicional, neste caso um estagiário de marketing para auxiliar a equipa em todos os esforços relacionados ao marketing com foco especial para pesquisa de marketing. Isso criou o cenário adequado para um estágio na área de Negócios Internacionais, uma vez que permitiu analisar o desenvolvimento e a evolução de uma jovem startup tecnológica num país estrangeiro. Os conhecimentos adquiridos durante os módulos teóricos regulares das aulas de Mestrado em Negócios Internacionais forneceram as ferramentas necessárias para avaliar a saúde de uma empresa internacional / start-up e a visão para fornecer conselhos sobre quais seriam as melhores sugestões para aumentar a produtividade, desenvolvimento e desenvolvimento. e como desenvolver uma pesquisa de mercado precisa. Com isso em mente, este relatório de estágio será concentrado na avaliação dos fatores atuais que estão limitando o desenvolvimento e o potencial de crescimento de startups tecnologicamente orientadas. Ao identificá-los, analisá-los e compará-los com os o que nos diz a pesquisa bibliográfica sobre a falta de start-up tecnológico, esperamos contribuir para a literatura atual. Além disso, sugeriremos um plano de ação para reduzir a influência dos fatores negativos para garantir uma melhor taxa de sobrevivência para o início dos próximos anos

Design, analysis and implementation of advanced methodologies to measure the socio-economic impact of personal data in large online services

El ecosistema web es enorme y, en general, se sustenta principalmente en un atributo intangible que sostiene la mayoría de los servicios gratuitos: la explotación de la información personal del usuario. A lo largo de los años, la preocupación por la forma en que los servicios utilizan los datos personales ha aumentado y atraído la atención de los medios de comunicación, gobiernos, reguladores y también de los usuarios. Esta recogida de información personal es hoy en día la principal fuente de ingresos en Internet. Además, por si fuera poco, la publicidad online es la pieza que lo sustenta todo. Sin la existencia de datos personales en comunión con la publicidad online, Internet probablemente no sería el gigante que hoy conocemos. La publicidad online es un ecosistema muy complejo en el que participan múltiples actores. Es el motor principal que genera ingresos en la red, y en pocos años ha evolucionado hasta llegar a miles de millones de usuarios en todo el mundo. Mientras navegan, los usuarios generan datos muy valiosos sobre sí mismos que los anunciantes utilizan después para ofrecerles productos relevantes en los que podrían estar interesados. Se trata de un enfoque bidireccional, ya que los anunciantes pagan a intermediarios para que muestren anuncios al público que, en principio, está más interesado. Sin embargo, este comercio, intercambio y tratamiento de datos personales, además de abrir nuevas vías de publicidad, exponen la privacidad de los usuarios. Esta incesante recopilación y comercialización de la información personal suele quedar tras un muro opaco, donde el usuario generalmente desconoce para qué se utilizan sus datos. Las iniciativas de privacidad y transparencia se han incrementado a lo largo de los años para empoderar al usuario en este negocio que mueve miles de millones de dólares en ingresos. No en vano, tras varios escándalos, como el de Facebook Cambridge Analytica, las empresas y los reguladores se han unido para crear transparencia y proteger a los usuarios de las malas prácticas derivadas del uso de su información personal. Por ejemplo, el Reglamento General de Protección de Datos, es el ejemplo más prometedor de regulación, que afecta a todos los estados miembros de la Unión Europea, abogando por la protección de los usuarios. El contenido de esta tesis tomará como referencia esta legislación. Por todo ello, el propósito de esta tesis consiste en aportar herramientas y metodologías que pongan de manifiesto usos inapropiados de datos personales por las grandes compañías del ecosistema publicitario online, y cree transparencia entre los usuarios, proporcionando, a su vez, soluciones para que se protejan. Así pues, el contenido de esta tesis ofrece diseño, análisis e implementación de metodologías que miden el impacto social y económico de la información personal online en los servicios extensivos de Internet. Principalmente, se centra en Facebook, una de las mayores redes sociales y servicios en la web, que cuenta con más de 2,8B de usuarios en todo el mundo y generó unos ingresos solo en publicidad online de más de 84 mil millones de dólares en el año 2020. En primer lugar, esta tesis presenta una solución, en forma de extensión del navegador llamada FDVT (Data Valuation Tool for Facebook users), para proporcionar a los usuarios una estimación personalizada y en tiempo real del dinero que están generando para Facebook. Analizando el número de anuncios e interacciones en una sesión, el usuario obtiene información sobre su valor dentro de esta red social. La extensión del navegador ha tenido una importante repercusión y adopción tanto por parte de los usuarios, instalándose más de 10k veces desde su lanzamiento público en octubre de 2016, como de los medios de comunicación, apareciendo en más de 100 medios. En segundo lugar, el estudio e investigación de los posibles riesgos asociados al tratamiento de los datos de los usuarios debe seguir también a la creación de este tipo de soluciones. En este contexto, esta tesis descubre y desvela resultados impactantes sobre el uso de la información personal: (i) cuantifica el número de usuarios afectados por el uso de atributos sensibles utilizados para la publicidad en Facebook, utilizando como referencia la definición de datos sensibles del Reglamento General de Protección de Datos. Esta tesis se basa en el uso de Procesamiento de Lenguaje Natural para identificar los atributos sensibles, y posteriormente utiliza el la plataforma de creación de anuncios de Facebook para recuperar el número de usuarios asignados con esta información sensible. Dos tercios de los usuarios de Facebook se ven afectados por el uso de datos personales sensibles que se les atribuyen. Además, la legislación parece no tener efecto en este uso de atributos sensibles por parte de Facebook, y presenta graves riesgos para los usuarios. (ii) Se modela cuál es el número de atributos que no identifican a priori personalmente al usuario y que aun así son suficientes para identificar de forma única a un individuo sobre una base de datos de miles de millones de usuarios, y se demuestra que llegar a un solo usuario es plausible incluso sin conocer datos que lo identifiquen personalmente de ellos mismos. Los resultados demuestran que 22 intereses al azar de un usuario son suficientes para identificarlo unívocamente con un 90% de probabilidad, y 4 si tomamos los menos populares. Por último, esta tesis se ha visto afectada por el estallido de la pandemia del COVID- 19, lo que ha contribuido al análisis de la evolución del mercado de la publicidad en línea con este periodo. La investigación demuestra que el mercado de la publicidad muestra una inelasticidad casi perfecta en la oferta y que cambió su composición debido a un cambio en el comportamiento en línea de los usuarios. También ilustra el potencial que tiene la utilización de los datos de los grandes servicios en línea, dado que ya tienen una alta tasa de adopción, y presenta un protocolo para la localización de contactos que han estado potencialmente expuestos a personas que direon positivo en COVID-19, en contraste con el fracaso de las nuevas aplicaciones de localización de contactos. En conclusión, la investigación de esta tesis muestra el impacto social y económico de la publicidad online y de los grandes servicios online en los usuarios. La metodología utilizada y desplegada sirve para poner de manifiesto y cuantificar los riesgos derivados de los datos personales en los servicios en línea. Presenta la necesidad de tales herramientas y metodologías en consonancia con la nueva legislación y los deseos de los usuarios. Siguiendo estas peticiones, en la búsqueda de transparencia y privacidad, esta tesis muestra soluciones y medidas fácilmente implementables para prevenir estos riesgos y capacitar al usuario para controlar su información personal.The web ecosystem is enormous, and overall it is sustained by an intangible attribute that mainly supports the majority of free services: the exploitation of personal information. Over the years, concerns on how services use personal data have increased and attracted the attention of media and users. This collection of personal information is the primary source of revenue on the Internet nowadays. Furthermore, on top of this, online advertising is the piece that supports it all. Without the existence of personal data in communion with online advertising, the Internet would probably not be the giant we know today. Online advertising is a very complex ecosystem in which multiple stakeholders take part. It is the motor that generates revenue on the web, and it has evolved in a few years to reach billions of users worldwide. While browsing, users generate valuable data about themselves that advertisers later use to offer them relevant products in which users could be interested. It is a two-way approach since advertisers pay intermediates to show ads to the public that is, in principle, most interested. However, this trading, sharing, and processing of personal data and behavior patterns, apart from opening up new advertising ways, expose users’ privacy. This incessant collection and commercialization of personal information usually fall behind an opaque wall, where the user often does not know what their data is used for. Privacy and transparency initiatives have increased over the years to empower the user in this business that moves billions of US dollars in revenue. Not surprisingly, after several scandals, such as the Facebook Cambridge Analytica scandal, businesses and regulators have joined forces to create transparency and protect users against the harmful practices derived from the use of their personal information. For instance, the General Data Protection Regulation (GDPR), is the most promising example of a data protection regulation, affecting all the member states of the European Union (EU), advocating for protecting users. The content of this thesis will use this legislation as a reference. For all these reasons, the purpose of this thesis is to provide tools and methodologies that reveal inappropriate uses of personal data by large companies in the online advertising ecosystem and create transparency among users, providing solutions to protect themselves. Thus, the content of this thesis offers design, analysis, and implementation of methodologies that measure online personal information’s social and economic impact on extensive Internet services. Mainly, it focuses on Facebook (FB), one of the largest social networks and services on the web, accounting with more than 2.8B Monthly Active Users (MAU) worldwide and generating only in online advertising revenue, more than $84B in 2020. First, this thesis presents a solution, in the form of a browser extension called Data Valuation Tool for Facebook users (FDVT), to provide users with a personalized, real-time estimation of the money they are generating for FB. By analyzing the number of ads and interactions in a session, the user gets information on their value within this social network. The add-on has had significant impact and adoption both by users, being installed more than 10k times since its public launch in October 2016, and media, appearing in more than 100 media outlets. Second, the study and research of the potential risks associated with processing users’ data should also follow the creation of these kinds of solutions. In this context, this thesis discovers and unveils striking results on the usage of personal information: (i) it quantifies the number of users affected by the usage of sensitive attributes used for advertising on FB, using as reference the definition of sensitive data from the GDPR. This thesis relies on the use of Natural Language Processing (NLP) to identify sensitive attributes, and it later uses the FB Ads Manager to retrieve the number of users assigned with this sensitive information. Two-thirds of FB users are affected by the use of sensitive personal data attributed to them. Moreover, the legislation seems not to affect this use of sensitive attributes from FB, and it presents severe risks to users. (ii) It models the number of non-Personal Identifiable Information (PII) attributes that are enough to uniquely identify an individual over a database of billions of users and proofs that reaching a single user is plausible even without knowing PII data of themselves. The results demonstrate that 22 interests at random from a user are enough to identify them uniquely with a 90% of probability, and 4 when taking the least popular ones. Finally, this thesis was affected by the outbreak of the COVID-19 pandemic what led to side contribute to the analysis of how the online advertising market evolved during this period. The research shows that the online advertising market shows an almost perfect inelasticity on supply and that it changed its composition due to a change in users’ online behavior. It also illustrates the potential of using data from large online services which already have a high adoption rate and presents a protocol for contact tracing individuals who have been potentially exposed to people who tested positive in COVID-19, in contrast to the failure of newly deployed contact tracing apps. In conclusion, the research for this thesis showcases the social and economic impact of online advertising and extensive online services on users. The methodology used and deployed is used to highlight and quantify the risks derived from personal data in online services. It presents the necessity of such tools and methodologies in line with new legislation and users’ desires. Following these requests, in the search for transparency and privacy, this thesis displays easy implementable solutions and measurements to prevent these risks and empower the user to control their personal information.This work was supported by the Ministerio de Educación, Cultura y Deporte, Spain, through the FPU Grant FPU16/05852, the Ministerio de Ciencia e Innovación, Spain, through the project ACHILLES Grant PID2019-104207RB-I00, the H2020 EU-Funded SMOOTH project under Grant 786741, and the H2020 EU-Funded PIMCITY project under Grant 871370.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: David Larrabeiti López.- Secretario: Gregorio Ignacio López López.- Vocal: Noel Cresp

Designing Local Energy Market Applications

Local energy markets and corresponding information systems are a way to integrate and involve residential customers in the energy transition, which can increase acceptance and drive private investment. This study is focused on the generation of design knowledge for these local energy market user applications in general and specifically to ensure long-term user engagement, which is a crucial success factor to maintain long-term effects. To this end, we derive, instantiate and evaluate seven design principles based on a field implementation with user interaction over 13 months using a design science research approach. The design principles and their instantiations are evaluated based on semi-structured interviews with the participants and a consecutive online experiment. The design principles provide fundamental knowledge for the setup of local energy market user applications and are therefore of value for researchers and practitioners alike