Convergence and knowledge processing in multi-agent systems

Multi-agent systems are complex systems comprised of multiple intelligent agents that act either independently or in cooperation with one another. Agent-based modelling is a method for studying complex systems like economies, societies, ecologies etc. Due to their complexity, very often mathematical analysis is limited in its ability to analyse such systems. In this case, agent-based modelling offers a practical, constructive method of analysis. The objective of this book is to shed light on some emergent properties of multi-agent systems. The authors focus their investigation on the effect of knowledge exchange on the convergence of complex, multi-agent systems.

Internationalization of small and medium sized UK manufacturing enterprises:technology and knowledge transfer perspective

This dissertation examines internationalisation of small and medium sized enterprises. There has been a journey to achieve this. The research has started as an action research as Teaching Company Scheme Associate. This has been done in two research cycles, which investigated factors for successful internationalisation of a small and medium sized UK manufacturing enterprise. This has revealed that successful internationalisation requires good technology and knowledge transfer to the new operations. The action research is followed by a survey that has been conducted within UK manufacturing companies. The data collected was analysed under three models: entry mode selection, role of factory and level of internationalisation. The first two models explain two major aspects of internationalisation decision. The last is showing what makes successful internationalising small and medium sized companies. These models provided several important results. The small and medium sized enterprise internationalisation is harder to achieve because most of these organisations do not have experience in technology and knowledge transfer. The success of internationalisation depends on the success of the transfer. This is achieved through employee ownership of the new knowledge. There are many factors affecting this result such as the network relationships such as trust, control and commitment and cognitive distance between two organisations. The last is a product of the difference between prior knowledge and the required level of knowledge. The entry mode and role of factory are decided through these factors while the level of internationalisation can only be explained by absorptive capacity of the recipient organisation and the technology transfer ability of the host organisation.

Educating the iPod generation:undergraduate attitudes, experiences and knowledge of vodcast and podcast use

There is an increasing pressure on university staff to provide ever more information and resources to students. This study investigated student opinions on (audio) podcasts and (video) vodcasts and how well they met requirements and aided learning processes. Two experiments within the Aston University looked at student opinion on, and usage of, podcasts and vodcasts for a selection of their psychology lectures. Recordings were produced first using a hand-held camcorder, and then using the in-house media department. WebCT was used to distribute the podcasts and vodcasts, attitude questionnaires were then circulated at two time points. Overall students indicated that podcasts and vodcasts were a beneficial addition resource for learning, particularly when used in conjunction with lecturers’ slides and as a tool for revision/assessment. The online material translated into students having increased understanding of the material, which supplemented and enhanced their learning without being a substitute for traditional lectures. There is scope for the provision of portable media files to become standard practice within higher education; integrating distance and online learning with traditional approaches to improve teaching and learning.

Country strategic risk and knowledge management:a proposed framework for improvement

The world is in a period of reflection about social and economic models. In particular there is a review of the capacities that countries have for improving their competitiveness. The experiences in a society are part of the process of learning and knowledge development in that society: especially in the development of communities. Risks appear continually in the process of the search for, analysis and implementation of solutions to problems. This paper discusses the issues related to the improvement of productivity and knowledge in a society, the risk that poor or even declining productivity brings to the communities and the need to develop people that support the decision making process in communities.The approach to improve the communities' development is through the design of a research programme in knowledge management based on distance learning. The research programme implementation is designed to provide value added to the decisions in communities in order to use collective intelligence, solve collective problems and to achieve goals that support local solutions. This program is organized and focused on four intelligence areas, artificial, collective, sentient and strategic. These areas are productivity related and seek to reduce the risk of lack of competitiveness through formal and integrated problem analysis. In a country such as Colombia, where different regions face varying problems to solve and there is a low level of infrastructure, the factors of production such as knowledge, skilled labour and "soft" infrastructure can be a way to develop the society.This entails using the local physical resources adequately for creating value with the support of people in the region to lead the analysis and search for solutions in the communities. The paper will describe the framework and programme and suggest how it could be applied in Colombia.

Decision support based on genomics:integration of data-and knowledge-driven reasoning

The breadth and depth of available clinico-genomic information, present an enormous opportunity for improving our ability to study disease mechanisms and meet the individualised medicine needs. A difficulty occurs when the results are to be transferred 'from bench to bedside'. Diversity of methods is one of the causes, but the most critical one relates to our inability to share and jointly exploit data and tools. This paper presents a perspective on current state-of-the-art in the analysis of clinico-genomic data and its relevance to medical decision support. It is an attempt to investigate the issues related to data and knowledge integration. Copyright © 2010 Inderscience Enterprises Ltd.

Eigen-Adaptation and Distributed Representation of 2-D Phase, Energy, Scale and Orientation in Spatial Vision

Distributed representations (DR) of cortical channels are pervasive in models of spatio-temporal vision. A central idea that underpins current innovations of DR stems from the extension of 1-D phase into 2-D images. Neurophysiological evidence, however, provides tenuous support for a quadrature representation in the visual cortex, since even phase visual units are associated with broader orientation tuning than odd phase visual units (J.Neurophys.,88,455–463, 2002). We demonstrate that the application of the steering theorems to a 2-D definition of phase afforded by the Riesz Transform (IEEE Trans. Sig. Proc., 49, 3136–3144), to include a Scale Transform, allows one to smoothly interpolate across 2-D phase and pass from circularly symmetric to orientation tuned visual units, and from more narrowly tuned odd symmetric units to even ones. Steering across 2-D phase and scale can be orthogonalized via a linearizing transformation. Using the tiltafter effect as an example, we argue that effects of visual adaptation can be better explained by via an orthogonal rather than channel specific representation of visual units. This is because of the ability to explicitly account for isotropic and cross-orientation adaptation effect from the orthogonal representation from which both direct and indirect tilt after-effects can be explained.

Firms’ innovation objectives and knowledge acquisition strategies:a comparative analysis

External partnerships play an important role in firms’ acquisition of the knowledge inputs to innovation. Such partnerships may be interactive – involving exploration and mutual learning by both parties – or non-interactive – involving exploitative activity and learning by only one party. Examples of non-interactive partnerships are copying or imitation. Here, we consider how firms’ innovation objectives influence their choice of interactive and/or non-interactive connections. We conduct a comparative analysis for the economies of Spain and the UK, which have contrasting innovation eco-systems and regulation burdens.

Knowledge based improvement:simulation and artificial intelligence for identifying and improving human decision-making in an operations systems

The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as 'knowledge-based improvement' (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent decision-making. By linking the VIS and AI representation, it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant.

The limits of open innovation:openness and (quasi-)markets in the organization of innovation

Recent studies have stressed the importance of ‘open innovation’ as a means of enhancing innovation performance. The essence of the open innovation model is to take advantage of external as well as internal knowledge sources in developing and commercialising innovation, so avoiding an excessively narrow internal focus in a key area of corporate activity. Although the external aspect of open innovation is often stressed, another key aspect involves maximising the flow of ideas and knowledge from different sources within the firm, for example through knowledge sharing via the use of cross-functional teams. A fully open innovation approach would therefore combine both aspects i.e. cross-functional teams with boundary-spanning knowledge linkages. This suggests that there should be complementarities between the use cross-functional teams with boundary-spanning knowledge linkages i.e. the returns to implementing open innovation in one innovation activity is should be greater if open innovation is already in place in another innovation activity. However, our findings – based on a large sample of UK and German manufacturing plants – do not support this view. Our results suggest that in practice the benefits envisaged in the open innovation model are not generally achievable by the majority of plants, and that instead the adoption of open innovation across the whole innovation process is likely to reduce innovation outputs. Our results provide some guidance on the type of activities where the adoption of a market-based governance structure such as open innovation may be most valuable. This is likely to be in innovation activities where search is deterministic, activities are separable, and where the required level of knowledge sharing is correspondingly moderate – in other words those activities which are more routinized. For this type of activity market-based governance mechanisms (i.e. open innovation) may well be more efficient than hierarchical governance structures. For other innovation activities where outcomes are more uncertain and unpredictable and the risks of knowledge exchange hazards are greater, quasi-market based governance structures such as open innovation are likely to be subject to rapidly diminishing returns in terms of innovation outputs.

Strategic and operational risk in an international collaboration agency: a knowledge management solution

The International Cooperation Agency (identified in this article as IDEA) working in Colombia is one of the most important in Colombian society with programs that support gender rights, human rights, justice and peace, scholarships, aboriginal population, youth, afro descendants population, economic development in communities, and environmental development. The identified problem is based on the diversified offer of services, collaboration and social intervention which requires diverse groups of people with multiple agendas, ways to support their mandates, disciplines, and professional competences. Knowledge creation and the growth and sustainability of the organization can be in danger because of a silo culture and the resulting reduced leverage of the separate group capabilities. Organizational memory is generally formed by the tacit knowledge of the organization members, given the value of accumulated experience that this kind of social work implies. Its loss is therefore a strategic and operational risk when most problem interventions rely on direct work in the socio-economic field and living real experiences with communities. The knowledge management solution presented in this article starts first, with the identification of the people and groups concerned and the creation of a knowledge map as a means to strengthen the ties between organizational members; second, by introducing a content management system designed to support the documentation process and knowledge sharing process; and third, introducing a methodology for the adaptation of a Balanced Scorecard based on the knowledge management processes. These three main steps lead to a knowledge management “solution” that has been implemented in the organization, comprising three components: a knowledge management system, training support and promotion of cultural change.

The board of directors, executives and risk knowledge management

Enterprise Risk Management (ERM) and Knowledge Management (KM) both encompass top-down and bottom-up approaches developing and embedding risk knowledge concepts and processes in strategy, policies, risk appetite definition, the decision-making process and business processes. The capacity to transfer risk knowledge affects all stakeholders and understanding of the risk knowledge about the enterprise's value is a key requirement in order to identify protection strategies for business sustainability. There are various factors that affect this capacity for transferring and understanding. Previous work has established that there is a difference between the influence of KM variables on Risk Control and on the perceived value of ERM. Communication among groups appears as a significant variable in improving Risk Control but only as a weak factor in improving the perceived value of ERM. However, the ERM mandate requires for its implementation a clear understanding, of risk management (RM) policies, actions and results, and the use of the integral view of RM as a governance and compliance program to support the value driven management of the organization. Furthermore, ERM implementation demands better capabilities for unification of the criteria of risk analysis, alignment of policies and protection guidelines across the organization. These capabilities can be affected by risk knowledge sharing between the RM group and the Board of Directors and other executives in the organization. This research presents an exploratory analysis of risk knowledge transfer variables used in risk management practice. A survey to risk management executives from 65 firms in various industries was undertaken and 108 answers were analyzed. Potential relationships among the variables are investigated using descriptive statistics and multivariate statistical models. The level of understanding of risk management policies and reports by the board is related to the quality of the flow of communication in the firm and perceived level of integration of the risk policy in the business processes.

Before and after modelling:risk knowledge management is required

Risk and knowledge are two concepts and components of business management which have so far been studied almost independently. This is especially true where risk management is conceived mainly in financial terms, as, for example, in the banking sector. The banking sector has sophisticated methodologies for managing risk, such as mathematical risk modeling. However. the methodologies for analyzing risk do not explicitly include knowledge management for risk knowledge creation and risk knowledge transfer. Banks are affected by internal and external changes with the consequent accommodation to new business models new regulations and the competition of big players around the world. Thus, banks have different levels of risk appetite and policies in risk management. This paper takes into consideration that business models are changing and that management is looking across the organization to identify the influence of strategic planning, information systems theory, risk management and knowledge management. These disciplines can handle the risks affecting banking that arise from different areas, but only if they work together. This creates a need to view them in an integrated way. This article sees enterprise risk management as a specific application of knowledge in order to control deviation from strategic objectives, shareholders' values and stakeholders' relationships. Before and after a modeling process it necessary to find insights into how the application of knowledge management processes can improve the understanding of risk and the implementation of enterprise risk management. The article presents a propose methodology to contribute to providing a guide for developing risk modeling knowledge and a reduction of knowledge silos, in order to improve the quality and quantity of solutions related to risk inquiries across the organization.

Using HLT for acquiring, retrieving and publishing knowledge in AKT:position paper

AKT is a major research project applying a variety of technologies to knowledge management. Knowledge is a dynamic, ubiquitous resource, which is to be found equally in an expert's head, under terabytes of data, or explicitly stated in manuals. AKT will extend knowledge management technologies to exploit the potential of the semantic web, covering the use of knowledge over its entire lifecycle, from acquisition to maintenance and deletion. In this paper we discuss how HLT will be used in AKT and how the use of HLT will affect different areas of KM, such as knowledge acquisition, retrieval and publishing.