287 research outputs found

    On the integration of trust with negotiation, argumentation and semantics

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    Agreement Technologies are needed for autonomous agents to come to mutually acceptable agreements, typically on behalf of humans. These technologies include trust computing, negotiation, argumentation and semantic alignment. In this paper, we identify a number of open questions regarding the integration of computational models and tools for trust computing with negotiation, argumentation and semantic alignment. We consider these questions in general and in the context of applications in open, distributed settings such as the grid and cloud computing. © 2013 Cambridge University Press.This work was partially supported by the Agreement Technology COST action (IC0801). The authors would like to thank for helpful discussions and comments all participants in the panel on >Trust, Argumentation and Semantics> on 16 December 2009, Agia Napa, CyprusPeer Reviewe

    Interoperability of Enterprise Software and Applications

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    A conceptual data model promoting data-driven circular manufacturing

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    Circular economy (CE) paradigm fosters manufacturing companies’ sustainability taking place through different circular manufacturing (CM) strategies. These strategies allow companies to be internally committed to embrace circular values and to be externally aligned with several stakeholders not necessarily belonging to the same supply chain. Nevertheless, these CM strategies adoption is limited by heterogeneous barriers, among which the management and sharing of data and information remain the most relevant ones, bounding the decision-making process of manufacturers in CM. Moreover, the extant literature unveiled the need to structure data and information in a reference model to make them usable by manufacturers. Therefore, the goal of the present work is to propose a reference model by developing a conceptual data model to standardise and structure the necessary data in CM to support manufacturers’ decision-making process. Through this model, data and information to be gathered by manufacturers are elucidated, providing an overview of which ones should be managed internally, and shared externally, clarifying the presence of their mutual interdependencies. The model was conceptualised and developed relying on the extant literature and improved and validated through academic and industrial experts’ interviews

    A method for taxonomy development and its application in information systems

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    HOW DO ENTREPRENEURIAL FIRMS APPROPRIATE VALUE IN BIO DATA INFRASTRUCTURES: AN EXPLORATORY QUALITATIVE STUDY

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    Recent technological advances such as in genome sequencing have exploded bio data infra-structures including those that comprise of generic - anonymized or pseudonymized - data. As open data, the bio data infrastructures do not constrain the final application context for their data. Rather it is up to complementors, taking the role of digital entrepreneurs, to appropriate value from this data through their revenue streams while at the same time scaling their opera-tions and ventures. We undertake a qualitative explorative study of bio data ventures examining the tension of applying open generic genome data to specific contexts for customers while being able to scale their businesses. The study uses primary data from 26 interviews and secondary data to reveal six strategies that complementors use for value appropriation. We derive three mechanisms of appropriating value at different stages of the value chain for bio data analysis on open data infrastructures: data contextualizing, data decontextualizing, and data recontex-tualizing. The study sheds light to how bio data – which has received limited attention in infor-mation systems research – can be an important source of value appropriation in digital ecosys-tems

    Integration of e-business strategy for multi-lifecycle production systems

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    Internet use has grown exponentially on the last few years becoming a global communication and business resource. Internet-based business, or e-Business will truly affect every sector of the economy in ways that today we can only imagine. The manufacturing sector will be at the forefront of this change. This doctoral dissertation provides a scientific framework and a set of novel decision support tools for evaluating, modeling, and optimizing the overall performance of e-Business integrated multi-lifecycle production systems. The characteristics of this framework include environmental lifecycle study, environmental performance metrics, hyper-network model of integrated e-supply chain networks, fuzzy multi-objective optimization method, discrete-event simulation approach, and scalable enterprise environmental management system design. The dissertation research reveals that integration of e-Business strategy into production systems can alter current industry practices along a pathway towards sustainability, enhancing resource productivity, improving cost efficiencies and reducing lifecycle environmental impacts. The following research challenges and scholarly accomplishments have been addressed in this dissertation: Identification and analysis of environmental impacts of e-Business. A pioneering environmental lifecycle study on the impact of e-Business is conducted, and fuzzy decision theory is further applied to evaluate e-Business scenarios in order to overcome data uncertainty and information gaps; Understanding, evaluation, and development of environmental performance metrics. Major environmental performance metrics are compared and evaluated. A universal target-based performance metric, developed jointly with a team of industry and university researchers, is evaluated, implemented, and utilized in the methodology framework; Generic framework of integrated e-supply chain network. The framework is based on the most recent research on large complex supply chain network model, but extended to integrate demanufacturers, recyclers, and resellers as supply chain partners. Moreover, The e-Business information network is modeled as a overlaid hypernetwork layer for the supply chain; Fuzzy multi-objective optimization theory and discrete-event simulation methods. The solution methods deal with overall system parameter trade-offs, partner selections, and sustainable decision-making; Architecture design for scalable enterprise environmental management system. This novel system is designed and deployed using knowledge-based ontology theory, and XML techniques within an agent-based structure. The implementation model and system prototype are also provided. The new methodology and framework have the potential of being widely used in system analysis, design and implementation of e-Business enabled engineering systems
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