Knowledge transfer processes in PFI: identification of barriers and enablers

Increasingly, the UK’s Private Finance Initiative has created a demand for construction companies to transfer knowledge from one organization or project to another. Knowledge transfer processes in such contexts face many challenges, due to the many resulting discontinuities in the involvement of organisations, personnel and information flow. This paper empirically identifies the barriers and enablers that hinder or enhance the transfer of knowledge in PFI contexts, drawing upon a questionnaire survey of construction firms. The main findings show that knowledge transfer processes in PFIs are hindered by time constraints, lack of trust, and policies, procedures, rules and regulations attached to the projects. Nevertheless, the processes of knowledge transfer are enhanced by emphasising the value and importance of a supportive leadership, participation/commitment from the relevant parties, and good communication between the relevant parties. The findings have considerable relevance to understanding the mechanism of knowledge transfer between organizations, projects and individuals within the PFI contexts in overcoming the barriers and enhancing the enablers. Furthermore, practitioners and managers can use the findings to efficiently design knowledge transfer frameworks that can be used to overcome the barriers encountered while enhancing the enablers to improve knowledge transfer processes.

Knowledge transfer processes in PFI/PPP: critical success factors

Successful knowledge transfer is an important process which requires continuous improvement in today’s knowledge-intensive economy. However, improving knowledge transfer processes represents a challenge for construction practitioners due to the complexity of knowledge acquisition, codification and sharing. Although knowledge transfer is context based, understanding the critical success factors can lead to improvements in the transfer process. This paper seeks to identify and evaluate the most significant critical factors for improving knowledge transfer processes in Public Private Partnerships/Private Finance Initiatives (PPP/PFI) projects. Drawing upon a questionnaire survey of 52 construction firms located in the UK, data is analysed using Severity Index (SI) and Coefficient of Variation (COV), to examine and identify these factors in PPP/PFI schemes. The findings suggest that a supportive leadership, participation/commitment from the relevant parties, and good communication between the relevant parties are crucial to improving knowledge transfer processes in PFI schemes. Practitioners, managers and researchers can use the findings to efficiently design performance measures for analysing and improving knowledge transfer processes.

A practical approach for training dynamic recurrent neural networks: use of Apriori information

Presents a technique for incorporating a priori knowledge from a state space system into a neural network training algorithm. The training algorithm considered is that of chemotaxis and the networks being trained are recurrent neural networks. Incorporation of the a priori knowledge ensures that the resultant network has behaviour similar to the system which it is modelling.

Autobiographical memory and amnesia: using conceptual knowledge to ground the self

A case of retrograde amnesia, PJM, elucidated the relationship between self, episodic memory and autobiographical knowledge. Results from a variety of measures including the I Am Memory Task (IAM Task), where memories are cued by self-generated self concepts, demonstrate that PJM has a coherent, continuous sense of self, despite having lost episodic memories for an 18-month period. Her use of conceptual autobiographical knowledge, in episodic tasks and to support aspects of identity, shows how autobiographical knowledge can support the self when episodic memories are inaccessible. These results are discussed with relation to current neuropsychological models of self and memory.

On-farm management of rice genetic diversity: understanding farmers' knowledge on rice ecosystems and varietal development

The paper highlights the methodological development of identifying and characterizing rice (Oryza sativa L.) ecosystems and the varietal deployment process through participatory approaches. Farmers have intricate knowledge of their rice ecosystems. Evidence from Begnas (mid-hill) and Kachorwa (plain) sites in Nepal suggests that farmers distinguish ecosystems for rice primarily on the basis of moisture and fertility of soils. Farmers also differentiate the number, relative size and specific characteristics of each ecosystem within a given geographic area. They allocate individual varieties to each ecosystem, based on the principle of ‘best fit’ between ecosystem characteristics and varietal traits, indicating that competition between varieties mainly occurs within the ecosystems. Land use and ecosystems determine rice genetic diversity, with marginal land having fewer options for varieties than more productive areas. Modern varieties are mostly confined to productive land, whereas landraces are adapted to marginal ecosystems. Researchers need to understand the ecosystems and varietal distribution within ecosystems better in order to plan and execute programmes on agrobiodiversity conservation on-farm, diversity deployment, repatriation of landraces and monitoring varietal diversity. Simple and practical ways to elicit information on rice ecosystems and associated varieties through farmers’ group discussion at village level are suggested.

Changing standards revisited: children’s awareness and knowledge of features of written standard English at ages 10-11

This paper reports the findings of a small-scale research project which investigated the levels of awareness and knowledge of written standard English of 10 and 11 year old children in two English primary schools. The project involved repeating in 2010 a written questionnaire previously used with children in the same schools in three separate surveys in 1999, 2002 and 2005. Data from the latest survey are compared to those from the previous three. The analysis seeks to identify any changes over time in children’s ability to recognise non-standard forms and supply standard English alternatives, as well as their ability to use technical terms related to language variation. Differences between the performance of boys and girls and that of the two schools are also analysed. The paper concludes that the socio-economic context of the schools may be a more important factor than gender in variations over time identified in the data.

Issues in language and development in multilingual settings: a case-study of knowledge exchange and teacher education in South Africa

The quality of a country’s human-resource base can be said to determine its level of success in social and economic development. This study focuses on some␣of the major human-resource development issues that surround the implementation of South Africa’s policy of multilingualism in education. It begins by discussing the relationship between knowledge, language, and human-resource, social and economic development within the global cultural economy. It then considers the situation in South Africa and, in particular, the implications of that country’s colonial and neo-colonial past for attempts to implement the new policy. Drawing on the linguistic-diversity-in-education debate in the United Kingdom of the past three decades, it assesses the first phase of an in-service teacher-education programme that was carried out at the Project for Alternative Education in South Africa (PRAESA) based at the University of Cape Town. The authors identify key short- and long-term issues related to knowledge exchange in education in multilingual societies, especially concerning the use of African languages as mediums for teaching and learning.

Knowledge acquisition in supply chain partnerships: the role of power

Knowledge is recognised as an important source of competitive advantage and hence there has been increasing academic and practitioner interest in understanding and isolating the factors that contribute to effective knowledge transfer between supply chain actors. The literature identifies power as a salient contributor to the effective operation of a supply chain partnership. However, there is a paucity of empirical research examining how power among actors influences knowledge acquisition and in turn the performance of supply chain partners. The aim of this research is to address this gap by examining the relationship between power, knowledge acquisition and supply chain performance among the supply chain partners of a focal Chinese steel manufacturer. A structured survey was used to collect the necessary data. Two conceptually independent variables – ‘availability of alternatives’ and ‘restraint in the use of power’ – were used to assess actual and realised power, respectively. Controlling for contingencies, we found that the flow of knowledge increased when supply chain actors had limited alternatives and when the more powerful actor exercised restraint in the use of power. Moreover, we found a positive relationship between knowledge acquisition and supply chain performance. This paper enriches the literature by empirically extending our understanding of how power affects knowledge acquisition and performance.

An overview of the use of neural networks for data mining tasks

In the recent years, the area of data mining has been experiencing considerable demand for technologies that extract knowledge from large and complex data sources. There has been substantial commercial interest as well as active research in the area that aim to develop new and improved approaches for extracting information, relationships, and patterns from large datasets. Artificial neural networks (NNs) are popular biologically-inspired intelligent methodologies, whose classification, prediction, and pattern recognition capabilities have been utilized successfully in many areas, including science, engineering, medicine, business, banking, telecommunication, and many other fields. This paper highlights from a data mining perspective the implementation of NN, using supervised and unsupervised learning, for pattern recognition, classification, prediction, and cluster analysis, and focuses the discussion on their usage in bioinformatics and financial data analysis tasks. © 2012 Wiley Periodicals, Inc.

Representing the acquisition and use of energy by individuals in agent-based models of animal populations

Summary 1. Agent-based models (ABMs) are widely used to predict how populations respond to changing environments. As the availability of food varies in space and time, individuals should have their own energy budgets, but there is no consensus as to how these should be modelled. Here, we use knowledge of physiological ecology to identify major issues confronting the modeller and to make recommendations about how energy budgets for use in ABMs should be constructed. 2. Our proposal is that modelled animals forage as necessary to supply their energy needs for maintenance, growth and reproduction. If there is sufficient energy intake, an animal allocates the energy obtained in the order: maintenance, growth, reproduction, energy storage, until its energy stores reach an optimal level. If there is a shortfall, the priorities for maintenance and growth/reproduction remain the same until reserves fall to a critical threshold below which all are allocated to maintenance. Rates of ingestion and allocation depend on body mass and temperature. We make suggestions for how each of these processes should be modelled mathematically. 3. Mortality rates vary with body mass and temperature according to known relationships, and these can be used to obtain estimates of background mortality rate. 4. If parameter values cannot be obtained directly, then values may provisionally be obtained by parameter borrowing, pattern-oriented modelling, artificial evolution or from allometric equations. 5. The development of ABMs incorporating individual energy budgets is essential for realistic modelling of populations affected by food availability. Such ABMs are already being used to guide conservation planning of nature reserves and shell fisheries, to assess environmental impacts of building proposals including wind farms and highways and to assess the effects on nontarget organisms of chemicals for the control of agricultural pests. Keywords: bioenergetics; energy budget; individual-based models; population dynamics.

Identifying key knowledge needs for evidence-based conservation of wild insect pollinators: a collaborative cross-sectoral exercise

In response to evidence of insect pollinator declines, organisations in many sectors, including the food and farming industry, are investing in pollinator conservation. They are keen to ensure that their efforts use the best available science. We convened a group of 32 ‘conservation practitioners’ with an active interest in pollinators and 16 insect pollinator scientists. The conservation practitioners include representatives from UK industry (including retail), environmental non-government organisations and nature conservation agencies. We collaboratively developed a long list of 246 knowledge needs relating to conservation of wild insect pollinators in the UK. We refined and selected the most important knowledge needs, through a three-stage process of voting and scoring, including discussions of each need at a workshop. We present the top 35 knowledge needs as scored by conservation practitioners or scientists. We find general agreement in priorities identified by these two groups. The priority knowledge needs will structure ongoing work to make science accessible to practitioners, and help to guide future science policy and funding. Understanding the economic benefits of crop pollination, basic pollinator ecology and impacts of pesticides on wild pollinators emerge strongly as priorities, as well as a need to monitor floral resources in the landscape.

Motivations behind farmers’ pesticide use in Bangladesh rice farming

This paper addresses the motivations behind farmers’ pesticide use in two regions of Bangladesh. The paper considers farmers’ knowledge of arthropods and their perceptions about pests and pest damage, and identifies why many farmers do not use recommended pest management practices. We propose that using the novel approach of classifying farmers according to their motivations and constraints rather than observed pesticide use can improve training approaches and increase farmers’ uptake and retention of more appropriate integrated pest management technologies.

W(h)ither phonological awareness? Literate trainee teachers’ lack of stable knowledge about the sound structure of words

Recent national developments in the teaching of literacy in the early years in the UK mean that teachers need to have explicit fluent knowledge of the sound structure of the language and its relationship to orthography in order to teach reading effectively. In this study, a group of 38 graduate trainee primary teachers were given a pencil and paper test of phonological awareness as part of a course on teaching literacy. Results from the pencil and paper test were used as the basis of teaching about the sound structure of words. The test was repeated six months later. The results showed that they did not use a consistent system for segmenting words into component sounds. Though there was substantial improvement on second testing, many trainees still did not show evidence that they had yet developed sufficient insights into the sound structure of words to be able to teach children about phonemes with certainty. It is argued that student teachers need substantial explicit training and practice in manipulating the sound structure of words to enable them to teach this aspect of language confidently.

Knowledge-based clinical pathway for medical quality improvement

Clinical pathways have been adopted for various diseases in clinical departments for quality improvement as a result of standardization of medical activities in treatment process. Using knowledge-based decision support on the basis of clinical pathways is a promising strategy to improve medical quality effectively. However, the clinical pathway knowledge has not been fully integrated into treatment process and thus cannot provide comprehensive support to the actual work practice. Therefore this paper proposes a knowledgebased clinical pathway management method which contributes to make use of clinical knowledge to support and optimize medical practice. We have developed a knowledgebased clinical pathway management system to demonstrate how the clinical pathway knowledge comprehensively supports the treatment process. The experiences from the use of this system show that the treatment quality can be effectively improved by the extracted and classified clinical pathway knowledge, seamless integration of patient-specific clinical pathway recommendations with medical tasks and the evaluating pathway deviations for optimization.

Sometimes they use it, sometimes they don’t: an epistemological discussion of L2 morphological production and its use as a competence measurement

The main goal of all approaches to adult second language acquisition (SLA) is to accurately describe and explain the overall acquisition process. To accomplish this, SLA researchers must come to agree on some key issues. In this commentary, I defend the necessity of the competence/performance distinction and how this relates to why an examination of morphological production presents challenges for SLA research. I suggest that such a methodology is meaningful only when it is dovetailed with procedures that test for related syntactic/semantic knowledge.