Learning and organization in the knowledge-based information economy: Initial findings from a participatory action research case study

This paper reports on an ongoing, multiphase, project-based action learning and research project. In particular, it summarizes some aspects of the learning climate and outcomes for a case study company In the software industry, Using a participatory action research approach, the learning company framework developed by Pedler et al, (1997) is used to initiate critical reflection in the company at three levels: managing director, senior management team and technical and professional staff. As such, this is one of the first systematic attempts to apply this framework to the entire organization and to a company in the knowledge-based learning economy. Two sets of issues are of general concern to the company: internal issues surrounding the company's reward and recognition policies and practices and the provision of accounting and control information in a business relevant way to all levels of staff; and external issues concerning the extent to which the company and its members actively learn from other companies and effectively capture, disseminate and use information accessed by staff in boundary-spanning roles. The paper concludes with some illustrations of changes being introduced by the company as a result of the feedback on and discussion of these issues.

Knowledge-based risk assessment under uncertainty in engineering projects

In this paper we describe how an evidential-reasoner can be used as a component of risk assessment of engineering projects using a direct way of reasoning. Guan & Bell (1991) introduced this method by using the mass functions to express rule strengths. Mass functions are also used to express data strengths. The data and rule strengths are combined to get a mass distribution for each rule; i.e., the first half of our reasoning process. Then we combine the prior mass and the evidence from the different rules; i.e., the second half of the reasoning process. Finally, belief intervals are calculated to help in identifying the risks. We apply our evidential-reasoner on an engineering project and the results demonstrate the feasibility and applicability of this system in this environment.

Intelligent Assembly Time Analysis Using a Digital Knowledge-Based Approach

The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for intelligent time analysis of aircraft assembly processes within a digital manufacturing framework. A knowledge system is developed so that the design knowledge can be intelligently retrieved for implementing assembly time analysis automatically. A time estimation method based on MOST, is reviewed and employed. Knowledge capture, transfer and storage within the digital manufacturing environment are extensively discussed. Configured plantypes, GUIs and functional modules are designed and developed for the automated time analysis. An exemplar study using an aircraft panel assembly from a regional jet is also presented. Although the method currently focuses on aircraft assembly, it can also be well utilized in other industry sectors, such as transportation, automobile and shipbuilding. The main contribution of the work is to present a methodology that facilitates the integration of time analysis with design and manufacturing using a digital manufacturing platform solution.

Intellectual Property management in publicly funded R&D centres—A comparison of university-based and company-based research centres

Recent thinking on open innovation and the knowledge-based economy have stressed the importance of external knowledge sources in stimulating innovation. Policy-makers have recognised this, establishing publicly funded Centres of R&D Excellence with the objective of stimulating industry–science links and localised innovation spillovers. Here, we examine the contrasting IP management practices of a group of 18 university- and company-based R&D centres supported by the same regional programme. Our analysis covers all but one of the Centres supported by the programme and suggests marked contrasts between the IP strategies of the university-based and company-based centres. This suggests the potential for very different types of knowledge spillovers from publicly funded R&D centres based in different types of organisations, and a range of alternative policy approaches to the future funding of R&D centres depending on policy-makers’ objectives.

Assessing parenting capacity in child protection: towards a knowledge-based model

The assessment of parenting capacity continues to engender public concern in cases of suspected harm to children. This paper outlines a model for approaching this task based on the application of three key domains of knowledge in social work relating to facts, theory and practice wisdom. The McMaster Model of Family Assessment is identified out of this process and reworked to give it a sharper focus on parenting roles and responsibilities. Seven formative dimensions of parenting are then elicited and combined with an analytical process of identifying strengths, concerns, prospects for growth and impact on child outcomes. The resulting assessment framework, it is argued, adds rigour to professional judgements about parenting capacity and enhances formulations on risk in child protection.

Towards a knowledge-based approach for effective decision-making in railway safety

Purpose – This paper aims to contribute towards understanding how safety knowledge can be elicited from railway experts for the purposes of supporting effective decision-making. Design/methodology/approach – A consortium of safety experts from across the British railway industry is formed. Collaborative modelling of the knowledge domain is used as an approach to the elicitation of safety knowledge from experts. From this, a series of knowledge models is derived to inform decision-making. This is achieved by using Bayesian networks as a knowledge modelling scheme, underpinning a Safety Prognosis tool to serve meaningful prognostics information and visualise such information to predict safety violations. Findings – Collaborative modelling of safety-critical knowledge is a valid approach to knowledge elicitation and its sharing across the railway industry. This approach overcomes some of the key limitations of existing approaches to knowledge elicitation. Such models become an effective tool for prediction of safety cases by using railway data. This is demonstrated using passenger–train interaction safety data. Practical implications – This study contributes to practice in two main directions: by documenting an effective approach to knowledge elicitation and knowledge sharing, while also helping the transport industry to understand safety. Social implications – By supporting the railway industry in their efforts to understand safety, this research has the potential to benefit railway passengers, staff and communities in general, which is a priority for the transport sector. Originality/value – This research applies a knowledge elicitation approach to understanding safety based on collaborative modelling, which is a novel approach in the context of transport.

The development of University Technology Transfer stakeholder relationships at a regional level: Lessons for the future

The increasing importance placed upon regional development and the knowledge-based economy as economic growth stimuli has led to a changing role for Universities and their interaction with the business community through (though not limited to) the transfer of technology from academia to industry. With the emergence of Local Enterprise Partnerships (LEPs) replacing the Regional Development Agencies (RDAs), there is a need for policy and practice going forward to be clearly informed by a critique of TTO (Technology Transfer Office)–RDA stakeholder relationship in a lessons learned approach so that LEPs can benefit from a faster learning curve. Thus, the aim of this paper is to examine the stakeholder relationship between three regional universities in the context of its TTO and the RDA with a view to determining lessons learned for the emerging LEP approach. Although the issues raised are contextual, the abstracted stakeholder conceptualisation of the TTO–RDA relationship should enable wider generalisation of the issues raised beyond the UK. Stakeholder theory relationship and stage development models are used to guide a repeat interview study of the TTO and RDA stakeholder groupings. The findings, interpreted using combined category and stage based stakeholder models, show how the longitudinal development of the TTO–RDA stakeholder relationship for each case has progressed through different stakeholder pathways, and stages where specific targeting of funding was dependant on the stakeholder stage. Greater targeted policy and funding, based on the stakeholder relationship approach, led to the development of joint mechanisms and a closer alignment of performance measures between the TTO and the RDA. However, over-reliance on the unitary nature of the TTO–RDA relationship may lead to a lack of cultivation and dependency for funding from other stakeholders.

Drivers of sales performance: a contemporary meta-analysis. Have salespeople become knowledge brokers?

It has been 25 years since the publication of a comprehensive review of the full spectrum of salesperformance drivers. This study takes stock of the contemporary field and synthesizes empirical evidence from the period 1982–2008. The authors revise the classification scheme for sales performance determinants devised by Walker et al. (1977) and estimate both the predictive validity of its sub-categories and the impact of a range of moderators on determinant-sales performance relationships. Based on multivariate causal model analysis, the results make two major observations: (1) Five sub-categories demonstrate significant relationships with sales performance: selling-related knowledge (ß=.28), degree of adaptiveness (ß=.27), role ambiguity (ß=-.25), cognitive aptitude (ß=.23) and work engagement (ß=.23). (2) These sub-categories are moderated by measurement method, research context, and salestype variables. The authors identify managerial implications of the results and offer suggestions for further research, including the conjecture that as the world is moving toward a knowledge-intensive economy, salespeople could be functioning as knowledge-brokers. The results seem to back this supposition and indicate how it might inspire future research in the field of personal selling.

Sustainable Technoscientific Development and the Innovator Citizen

Sustainable development could provide a critical foil for individual
and especially collective reflection on the normative
direction, ends and means employed by societies, particularly
around the economy, its technology and resource-intensive
orientation and configuration with ecosystems. However,
although sustainable development is a constitutional objective
of the EU, its implementation in strategies and policies reveals
a much narrower meaning. By framing sustainable development
as ecological modernisation on the basis of technoscientific
innovation, and by imagining citizens as entrepreneurs in a
knowledge-based European economy, openings for democratic
experimentation and social innovation are limited and even
forestalled. In addition, the disruptive and transformational
potential of citizenship is stymied. Still, sustainable development
has resonance within citizenship and human rights
discourses that provide important resources for the fashioning
of common understanding. These are valuable supplements to
the repertoire of European citizenship that could help to embed
sustainable development in the social fabric and generate
alternative imaginaries and futures of a sustainable Europe.

A Characteristic Function Approach to Inconsistency Measures for Knowledge Bases.

Knowledge is an important component in many intelligent systems.
Since items of knowledge in a knowledge base can be conflicting, especially if
there are multiple sources contributing to the knowledge in this base, significant
research efforts have been made on developing inconsistency measures for
knowledge bases and on developing merging approaches. Most of these efforts
start with flat knowledge bases. However, in many real-world applications, items
of knowledge are not perceived with equal importance, rather, weights (which
can be used to indicate the importance or priority) are associated with items of
knowledge. Therefore, measuring the inconsistency of a knowledge base with
weighted formulae as well as their merging is an important but difficult task. In
this paper, we derive a numerical characteristic function from each knowledge
base with weighted formulae, based on the Dempster-Shafer theory of evidence.
Using these functions, we are able to measure the inconsistency of the knowledge
base in a convenient and rational way, and are able to merge multiple knowledge
bases with weighted formulae, even if knowledge in these bases may be
inconsistent. Furthermore, by examining whether multiple knowledge bases are
dependent or independent, they can be combined in different ways using their
characteristic functions, which cannot be handled (or at least have never been
considered) in classic knowledge based merging approaches in the literature.