949 resultados para Inter-organizational collaborative networks


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Open collaborative projects are moving to the foreground of knowledge production. Some online user communities develop into longterm projects that generate a highly valuable and at the same time freely accessible output. Traditional copyright law that is organized around the idea of a single creative entity is not well equipped to accommodate the needs of these forms of collaboration. In order to enable a peculiar network-type of interaction participants instead draw on public licensing models that determine the freedoms to use individual contributions. With the help of these access rules the operational logic of the project can be implemented successfully. However, as the case of the Wikipedia GFDL-CC license transition demonstrates, the adaptation of access rules in networks to new circumstances raises collective action problems and suffers from pitfalls caused by the fact that public licensing is grounded in individual copyright. Legal governance of open collaboration projects is a largely unexplored field. The article argues that the license steward of a public license assumes the position of a fiduciary of the knowledge commons generated under the license regime. Ultimately, the governance of decentralized networks translates into a composite of organizational and contractual elements. It is concluded that the production of global knowledge commons relies on rules of transnational private law.

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Previous literature in SIE (self-initiated expatriation) has been mostly focused on an individual perspective. Studies on SIEs in organizational context are scarce. The current paper sought to examine the effect of perceived organizational support (POS) on SIE employees’ intention to stay in the host country, mediated by career satisfaction. Furthermore, we examined the moderating roles of career-related social networks with host and home country nationals on the effectiveness of POS. Data from 112 SIE employees in Germany were collected and analyzed. Empirical results partially supported our proposed model: there were significant negative indirect effect between POS and intention to stay, when career network size with home country nationals was high. The direct effect between POS and intention to stay was positive. For HR practice, our paper gave insight to understand SIE employees’ needs for support and mobility preferences, which can help organizations to develop more targeted HR development measures and assignment strategies for them.

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Abstract The proliferation of wireless sensor networks and the variety of envisioned applications associated with them has motivated the development of distributed algorithms for collaborative processing over networked systems. One of the applications that has attracted the attention of the researchers is that of target localization where the nodes of the network try to estimate the position of an unknown target that lies within its coverage area. Particularly challenging is the problem of estimating the target’s position when we use received signal strength indicator (RSSI) due to the nonlinear relationship between the measured signal and the true position of the target. Many of the existing approaches suffer either from high computational complexity (e.g., particle filters) or lack of accuracy. Further, many of the proposed solutions are centralized which make their application to a sensor network questionable. Depending on the application at hand and, from a practical perspective it could be convenient to find a balance between localization accuracy and complexity. Into this direction we approach the maximum likelihood location estimation problem by solving a suboptimal (and more tractable) problem. One of the main advantages of the proposed scheme is that it allows for a decentralized implementation using distributed processing tools (e.g., consensus and convex optimization) and therefore, it is very suitable to be implemented in real sensor networks. If further accuracy is needed an additional refinement step could be performed around the found solution. Under the assumption of independent noise among the nodes such local search can be done in a fully distributed way using a distributed version of the Gauss-Newton method based on consensus. Regardless of the underlying application or function of the sensor network it is al¬ways necessary to have a mechanism for data reporting. While some approaches use a special kind of nodes (called sink nodes) for data harvesting and forwarding to the outside world, there are however some scenarios where such an approach is impractical or even impossible to deploy. Further, such sink nodes become a bottleneck in terms of traffic flow and power consumption. To overcome these issues instead of using sink nodes for data reporting one could use collaborative beamforming techniques to forward directly the generated data to a base station or gateway to the outside world. In a dis-tributed environment like a sensor network nodes cooperate in order to form a virtual antenna array that can exploit the benefits of multi-antenna communications. In col-laborative beamforming nodes synchronize their phases in order to add constructively at the receiver. Some of the inconveniences associated with collaborative beamforming techniques is that there is no control over the radiation pattern since it is treated as a random quantity. This may cause interference to other coexisting systems and fast bat-tery depletion at the nodes. Since energy-efficiency is a major design issue we consider the development of a distributed collaborative beamforming scheme that maximizes the network lifetime while meeting some quality of service (QoS) requirement at the re¬ceiver side. Using local information about battery status and channel conditions we find distributed algorithms that converge to the optimal centralized beamformer. While in the first part we consider only battery depletion due to communications beamforming, we extend the model to account for more realistic scenarios by the introduction of an additional random energy consumption. It is shown how the new problem generalizes the original one and under which conditions it is easily solvable. By formulating the problem under the energy-efficiency perspective the network’s lifetime is significantly improved. Resumen La proliferación de las redes inalámbricas de sensores junto con la gran variedad de posi¬bles aplicaciones relacionadas, han motivado el desarrollo de herramientas y algoritmos necesarios para el procesado cooperativo en sistemas distribuidos. Una de las aplicaciones que suscitado mayor interés entre la comunidad científica es la de localization, donde el conjunto de nodos de la red intenta estimar la posición de un blanco localizado dentro de su área de cobertura. El problema de la localization es especialmente desafiante cuando se usan niveles de energía de la seal recibida (RSSI por sus siglas en inglés) como medida para la localization. El principal inconveniente reside en el hecho que el nivel de señal recibida no sigue una relación lineal con la posición del blanco. Muchas de las soluciones actuales al problema de localization usando RSSI se basan en complejos esquemas centralizados como filtros de partículas, mientas que en otras se basan en esquemas mucho más simples pero con menor precisión. Además, en muchos casos las estrategias son centralizadas lo que resulta poco prácticos para su implementación en redes de sensores. Desde un punto de vista práctico y de implementation, es conveniente, para ciertos escenarios y aplicaciones, el desarrollo de alternativas que ofrezcan un compromiso entre complejidad y precisión. En esta línea, en lugar de abordar directamente el problema de la estimación de la posición del blanco bajo el criterio de máxima verosimilitud, proponemos usar una formulación subóptima del problema más manejable analíticamente y que ofrece la ventaja de permitir en¬contrar la solución al problema de localization de una forma totalmente distribuida, convirtiéndola así en una solución atractiva dentro del contexto de redes inalámbricas de sensores. Para ello, se usan herramientas de procesado distribuido como los algorit¬mos de consenso y de optimización convexa en sistemas distribuidos. Para aplicaciones donde se requiera de un mayor grado de precisión se propone una estrategia que con¬siste en la optimización local de la función de verosimilitud entorno a la estimación inicialmente obtenida. Esta optimización se puede realizar de forma descentralizada usando una versión basada en consenso del método de Gauss-Newton siempre y cuando asumamos independencia de los ruidos de medida en los diferentes nodos. Independientemente de la aplicación subyacente de la red de sensores, es necesario tener un mecanismo que permita recopilar los datos provenientes de la red de sensores. Una forma de hacerlo es mediante el uso de uno o varios nodos especiales, llamados nodos “sumidero”, (sink en inglés) que actúen como centros recolectores de información y que estarán equipados con hardware adicional que les permita la interacción con el exterior de la red. La principal desventaja de esta estrategia es que dichos nodos se convierten en cuellos de botella en cuanto a tráfico y capacidad de cálculo. Como alter¬nativa se pueden usar técnicas cooperativas de conformación de haz (beamforming en inglés) de manera que el conjunto de la red puede verse como un único sistema virtual de múltiples antenas y, por tanto, que exploten los beneficios que ofrecen las comu¬nicaciones con múltiples antenas. Para ello, los distintos nodos de la red sincronizan sus transmisiones de manera que se produce una interferencia constructiva en el recep¬tor. No obstante, las actuales técnicas se basan en resultados promedios y asintóticos, cuando el número de nodos es muy grande. Para una configuración específica se pierde el control sobre el diagrama de radiación causando posibles interferencias sobre sis¬temas coexistentes o gastando más potencia de la requerida. La eficiencia energética es una cuestión capital en las redes inalámbricas de sensores ya que los nodos están equipados con baterías. Es por tanto muy importante preservar la batería evitando cambios innecesarios y el consecuente aumento de costes. Bajo estas consideraciones, se propone un esquema de conformación de haz que maximice el tiempo de vida útil de la red, entendiendo como tal el máximo tiempo que la red puede estar operativa garantizando unos requisitos de calidad de servicio (QoS por sus siglas en inglés) que permitan una decodificación fiable de la señal recibida en la estación base. Se proponen además algoritmos distribuidos que convergen a la solución centralizada. Inicialmente se considera que la única causa de consumo energético se debe a las comunicaciones con la estación base. Este modelo de consumo energético es modificado para tener en cuenta otras formas de consumo de energía derivadas de procesos inherentes al funcionamiento de la red como la adquisición y procesado de datos, las comunicaciones locales entre nodos, etc. Dicho consumo adicional de energía se modela como una variable aleatoria en cada nodo. Se cambia por tanto, a un escenario probabilístico que generaliza el caso determinista y se proporcionan condiciones bajo las cuales el problema se puede resolver de forma eficiente. Se demuestra que el tiempo de vida de la red mejora de forma significativa usando el criterio propuesto de eficiencia energética.

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In the process of value creation, organizations perform an intense intra-organizational dialog through which internal VS alignment is achieved towards certain strategic objectives. Within the context of complex organizational networks, were goal conflicts are preprogrammed through incentive structures, VS alignment as legitimation of action towards strategic goals has special interest. On the one hand it facilitates the access to necessary resources for goal achievement and on the other it increases the sustainability and supports commonly agreed upon decisions leading to success. This paper provides a winnerless process (WLP) differential equations model for quantifying intra-organizational value stream (VS) alignment dynamics that can help design sustainable lean management solutions. This paper presents ongoing research results that show how the model was implemented in one industrial facility.

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The research team reviewed numerous several multi- sectoral entities and identified nine GGNs that became the subject of our case studies. The research team conducted semi-structured interviews with executives and staff from each of these GNNs and prepared a profile, including a description of the unique evolution of the organization, goals and objectives, organizational structure and governance arrangements for each GGN. The following list provides an overview of the nine GGNs profiled: 1. Every Woman Every Child is an unprecedented global effort that mobilizes and amplifies action by governments, multilaterals, the private sector, research centers, academia and civil society to address life-threatening health challenges facing women and children globally. 2. HERproject catalyzes global partnerships and local Networks to improve female workers’ general and reproductive health in eight emerging economies. 3. R4 Rural Resilience Initiative is a cutting-edge, strategic, large-scale partnership between the public and private sectors to innovate and develop better tools to help the world’s most vulnerable people build resilient livelihoods. 4. Extractive Industry Transparency Initiative is a coalition of governments, companies, civil society groups, investors and international organizations that aims to improve transparency and accountability in the extractives sector. 5. Global Network for Neglected Tropical Diseases works with international partners at the highest level of government, business and society to break down the logistical and financial barriers to delivering existing treatments for the seven most common neglected tropical diseases. 6. Global Alliance for Improved Nutrition is an alliance that supports public-private partnerships to increase access to the missing nutrients in diets necessary for people, communities and economies to be stronger and healthier. 7. Inter-Agency Network For Education in Emergencies is a global Network of individuals and representatives from NGOs, United Nations and donor agencies, governments, academic institutions, schools and affected populations working to ensure all persons have the right to a quality and safe education in emergencies and post- crisis recovery. 8. mHealth Alliance works with diverse partners to advance mobile-based or mobile-enhanced solutions that deliver health through research, advocacy, support for the development of interoperable solutions and sustainable deployment models. 9. The Rainforest Alliance is a global non-profit that focuses on environmental conservation and sustainable development and works through collaborative partnerships with various stakeholders.

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Network building and exchange of information by people within networks is crucial to the innovation process. Contrary to older models, in social networks the flow of information is noncontinuous and nonlinear. There are critical barriers to information flow that operate in a problematic manner. New models and new analytic tools are needed for these systems. This paper introduces the concept of virtual circuits and draws on recent concepts of network modelling and design to introduce a probabilistic switch theory that can be described using matrices. It can be used to model multistep information flow between people within organisational networks, to provide formal definitions of efficient and balanced networks and to describe distortion of information as it passes along human communication channels. The concept of multi-dimensional information space arises naturally from the use of matrices. The theory and the use of serial diagonal matrices have applications to organisational design and to the modelling of other systems. It is hypothesised that opinion leaders or creative individuals are more likely to emerge at information-rich nodes in networks. A mathematical definition of such nodes is developed and it does not invariably correspond with centrality as defined by early work on networks.

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Purpose – The purpose of this paper is to investigate how research and development (R&D) collaboration takes place for complex new products in the automotive sector. The research aims to give guidelines to increase the effectiveness of such collaborations. Design/methodology/approach – The methodology used to investigate this issue was grounded theory. The empirical data were collected through a mixture of interviews and questionnaires. The resulting inducted conceptual models were subsequently validated in industrial workshops. Findings – The findings show that frontloading of the collaborative members was a major issue in managing successful R&D collaborations. Research limitations/implications – The limitation of this research is that it is only based in the German automotive industry. Practical implications – Practical implications have come out of this research. Models and guidelines are given to help make a success of collaborative projects and their potential impacts on time, cost and quality metrics. Originality/value – Frontloading is not often studied in a collaborative manner; it is normally studied within just one organisation. This study has novel value because it has involved a number of different members throughout the supplier network.

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This paper presents the findings of a recently completed research project. It sheds light upon the appropriate governance of inter-firm relationships, in order to achieve competitive success for the whole partnership and its individual members. An exploratory study in the German automotive industry using inductive Grounded Theory was conducted, in order to form a set of propositions that were then validated. The research has resulted in the consolidation of these propositions into a novel concept termed Collaborative Enterprise Governance, which draws on an inter-disciplinary body of knowledge. The core of the concept is a competence based contingency framework that helps enterprise managers in selecting the most appropriate governance strategy (i.e. enterprise structure) for an inter-firm relationships within automotive supply networks (i.e. enterprises), depending on various exogenous and endogenous factors.

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This research reports on the appropriate governance, i.e. design and management, of inter-firm R&D relationships in order to achieve sustainable competitive success for the whole partnership as well as its individual members. An exploratory study in the German automotive industry using inductive Grounded Theory was conducted. This involved data collection via 28 semi-structured interviews with 16 companies in order to form a set of 35 tentative propositions that have been validated via a questionnaire survey receiving 110 responses from 52 companies. The research has resulted in the consolidation of the validated propositions into a novel concept termed Collaborative Enterprise Governance. The core of the concept is a competence based contingency framework that helps decision makers in selecting the most appropriate governance strategy (i.e. sourcing strategy) for an inter-firm R&D relationship between a buyer and its supplier. Thereby, the concept does not draw on whole company-to-company connectivity. It rather conceptualises an inter-firm relationship to be composed of autonomous cross-functional units of the individual partner companies that contribute value to a particular joint R&D project via the possession of task specific competencies. The novel concept and its elements have been evaluated in a focus group with industrial experts of the German automotive industry and revealed positive effects on the sustainable competitive success of the whole partnership and the individual partner companies. However, it also showed that current practice does not apply the right mechanisms for its implementation and hence guidelines for practitioners and decision makers involved in inter-firm R&D collaboration in the automotive industry are offered on how to facilitate the implementation and usage of the Collaborative Enterprise Governance philosophy.

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Congestion control is critical for the provisioning of quality of services (QoS) over dedicated short range communications (DSRC) vehicle networks for road safety applications. In this paper we propose a congestion control method for DSRC vehicle networks at road intersection, with the aims of providing high availability and low latency channels for high priority emergency safety applications while maximizing channel utilization for low priority routine safety applications. In this method a offline simulation based approach is used to find out the best possible configurations of message rate and MAC layer backoff exponent (BE) for a given number of vehicles equipped with DSRC radios. The identified best configurations are then used online by an roadside access point (AP) for system operation. Simulation results demonstrated that this adaptive method significantly outperforms the fixed control method under varying number of vehicles. The impact of estimation error on the number of vehicles in the network on system level performance is also investigated.

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Purpose – The literature on interfirm networks devotes scant attention to the ways collaborating firms combine and integrate the knowledge they share and to the subsequent learning outcomes. This study aims to investigate how motorsport companies use network ties to share and recombine knowledge and the learning that occurs both at the organizational and dyadic network levels. Design/methodology/approach – The paper adopts a qualitative and inductive approach with the aim of developing theory from an in-depth examination of the dyadic ties between motorsport companies and the way they share and recombine knowledge. Findings – The research shows that motorsport companies having substantial competences at managing knowledge flows do so by getting advantage of bridging ties. While bridging ties allow motorsport companies to reach distant and diverse sources of knowledge, their strengthening and the formation of relational capital facilitate the mediation and overlapping of that knowledge. Research limitations/implications – The analysis rests on a qualitative account in a single industry and does not take into account different types of inter-firm networks (e.g. alliances; constellations; consortia etc.) and governance structures. Cross-industry analyses may provide a more fine-grained picture of the practices used to recombine knowledge and the ideal composition of inter-firm ties. Practical implications – This study provides some interesting implications for scholars and managers concerned with the management of innovation activities at the interfirm level. From a managerial point of view, the recognition of the different roles played by network spanning connections is particularly salient and raises issues concerning the effective design and management of interfirm ties. Originality/value – Although much of the literature emphasizes the role of bridging ties in connecting to diverse pools of knowledge, this paper goes one step further and investigates in more depth how firms gather and combine distant and heterogeneous sources of knowledge through the use of strengthened bridging ties and a micro-context conducive to high quality relationships.

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Recommender systems are now widely used in e-commerce applications to assist customers to find relevant products from the many that are frequently available. Collaborative filtering (CF) is a key component of many of these systems, in which recommendations are made to users based on the opinions of similar users in a system. This paper presents a model-based approach to CF by using supervised ARTMAP neural networks (NN). This approach deploys formation of reference vectors, which makes a CF recommendation system able to classify user profile patterns into classes of similar profiles. Empirical results reported show that the proposed approach performs better than similar CF systems based on unsupervised ART2 NN or neighbourhood-based algorithm.