Decision-focussed resource modelling for design decision support

Resource management including resource allocation, levelling, configuration and monitoring has been recognised as critical to design decision making. It has received increasing research interests in recent years. Different definitions, models and systems have been developed and published in literature. One common issue with existing research is that the resource modelling has focussed on the information view of resources. A few acknowledged the importance of resource capability to design management, but none has addressed the evaluation analysis of resource fitness to effectively support design decisions. This paper proposes a decision-focused resource model framework that addresses the combination of resource evaluation with resource information from multiple perspectives. A resource management system constructed on the resource model framework can provide functions for design engineers to efficiently search and retrieve the best fit resources (based on the evaluation results) to meet decision requirements. Thus, the system has the potential to provide improved decision making performance compared with existing resource management systems

Coordination approaches and systems - part I : a strategic perspective

This is the first part of a two-part paper presenting a fundamental review and summary of research of design coordination and cooperation technologies. The theme of this review is aimed at the research conducted within the decision management aspect of design coordination. The focus is therefore on the strategies involved in making decisions and how these strategies are used to satisfy design requirements. The paper reviews research within collaborative and coordinated design, project and workflow management, and, task and organization models. The research reviewed has attempted to identify fundamental coordination mechanisms from different domains, however it is concluded that domain independent mechanisms need to be augmented with domain specific mechanisms to facilitate coordination. Part II is a review of design coordination from an operational perspective

Knowledge assimilation processes of rapidly internationalising firms: longitudinal case studies of Scottish SMEs

<p>Purpose – The accumulation of knowledge and learning by firms has been identified as being critical to their internationalisation. This paper aims to explore the knowledge assimilation processes of rapidly internationalising small to medium-sized enterprises (SMEs).</p> <p>Design/methodology/approach – This is a qualitative enquiry in two stages. First, four case studies were selected from firms that were participating in an internationalisation programme run by Scottish Enterprise, the regional development agency. Data collection involved semi-structured interviews with chief executive officers (CEOs) and programme providers, and archival data. Second, two focus groups were held with six CEOs participating in the programme.</p> <p>Findings – The findings indicate that knowledge sharing is important for rapidly internationalising SMEs and that firms adopted high levels of formality in assimilating knowledge. Two key aspects of formality were identified as important; formal planned events to share explicit and tacit knowledge and the codification of tacit to explicit knowledge. Knowledge may be assimilated less formally by the retention of tacit knowledge as tacit, while utilising elements of formality. The paper finds that learning for internationalisation can be transferred to support domestic growth.</p> <p>Practical implications – It is important for firms to develop appropriate knowledge assimilation processes within their management systems to support internationalisation. The CEO and management team need to take the lead in marshalling commitment to learning processes and in cultivating an organisational culture that is supportive of learning.</p> <p>Originality/value – This research contributes to international entrepreneurship by providing insights into the knowledge assimilation processes employed by rapidly internationalising SMEs to manage the tensions between the need for greater formality to be efficient at learning, and informality to enable speedy decision making.</p&gt

Deriving Information Requirements from Responsibility Models

This paper describes research in understanding the requirements for complex information systems that are constructed from one or more generic COTS systems. We argue that, in these cases, behavioural requirements are largely defined by the underlying system and that the goal of the requirements engineering process is to understand the information requirements of system stakeholders. We discuss this notion of information requirements and propose that an understanding of how a socio-technical system is structured in terms of responsibilities is an effective way of discovering this type of requirement. We introduce the idea of responsibility modelling and show, using an example drawn from the domain of emergency planning, how a responsibility model can be used to derive information requirements for a system that coordinates the multiple agencies dealing with an emergency

Can models of agents be transferred between different areas?

One of the main reasons for the sustained activity and interest in the field of agent-based systems, apart from the obvious recognition of its value as a natural and intuitive way of understanding the world, is its reach into very many different and distinct fields of investigation. Indeed, the notions of agents and multi-agent systems are relevant to fields ranging from economics to robotics, in contributing to the foundations of the field, being influenced by ongoing research, and in providing many domains of application. While these various disciplines constitute a rich and diverse environment for agent research, the way in which they may have been linked by it is a much less considered issue. The purpose of this panel was to examine just this concern, in the relationships between different areas that have resulted from agent research. Informed by the experience of the participants in the areas of robotics, social simulation, economics, computer science and artificial intelligence, the discussion was lively and sometimes heated