Organisational knowledge integration: towards a conceptual framework

This study analyses organisational knowledge integration processes from a multi-level and systemic perspective, with particular reference to the case of Fujitsu. A conceptual framework for knowledge integration is suggested focusing on team-building capability, capturing and utilising individual tacit knowledge, and communication networks for integrating dispersed specialist knowledge required in the development of new products and services. The research highlights that knowledge integration occurring in the innovation process is a result of knowledge exposure, its distribution and embodiment and finally its transfer, which leads to innovation capability and competitive advantage in firm.

The applicability of aesthetic knowledge in organizational decision making processes

We argue that aesthetic knowledge, which is a form of tacit knowledge of beauty and related concepts, is an important, yet under-researched, topic in the study of organizational decision making processes. The significance of aesthetic knowledge for decision making processes is derived from its universal application by humans to commonplace practices; its use as the basis of decision criteria in complex situations to which the effective application of logic and reason is difficult; and its role both in assisting cognition in general and in enabling the choice of solutions generated from rational decision making processes. Despite its importance, the empirical research examining the application of aesthetic knowledge in organizational decision making processes is limited. Further detailed study of aesthetic knowledge in the context of organizational decision making processes is required to extend the recent movement in the field aimed at examining the role that extrarational, human-centered factors play in organizational decisions.

Creative industries and innovation in a knowledge economy

The cultural and creative industries contribute to the knowledge economy by their role in reproducing cultural knowledge and through provision of entertainment, experience and leisure goods with cultural content, for which they are widely acknowledged as suffering serious market failure problems (Baumol and Bowen, 1966; Throsby and Withers, 1979). But they also contribute to the innovation process, an aspect that has only recently been appreciated. Specifically, the creative industries are a driver of the knowledge economy by their contribution to the innovation process on the demand side of consumer uptake of new ideas and by their facilitation of consumer-producer interaction. The creative industries are, in this respect, a legitimate part of the innovation system of a knowledge economy.

Knowledge is People Doing Things, Knowledge Economies Are People Doing Things with Better Outcomes for More People

Description ‘The second volume of the Handbook on the Knowledge Economy is a worthy companion to the highly successful original volume published in 2005, extending its theoretical depth and developing its coverage. Together the two volumes provide the single best work and reference point for knowledge economy studies. The second volume with fifteen original essays by renowned scholars in the field, provides insightful and robust analyses of the development potential of the knowledge economy in all its aspects, forms and manifestations.’ – Michael A. Peters, University of Illinois, US

A world map of knowledge in the making : Wikipedia's Inter-Language Linkage as a dependency explorer of global knowledge accumulation

Analysis of Wikipedia's inter-language links provides insight into a new mechanism of knowledge sharing and linking worldwide.

Teachers' knowledge for social education : perspectives from the middle years of schooling

Social education in Australia is a divisive educational issue. The last decade has been marked by the controversial integrated social studies curriculum, Studies of Society and Environment (SOSE) where history, geography and environmental studies were integrated with civics and citizenship. The introduction of a compulsory K-10 Australian Curriculum from 2011, however, marks the return to history and geography and the abandonment of SOSE. Curriculum reform aside, what do teachers think is essential knowledge for middle years social education? The paper reports on a phenomenographical exploration of thirty-one middle school teachers’ conceptions of essential knowledge for SOSE. Framed by Shulman’s (1986, 1987) theoretical framework of the knowledge base for teaching, the research identified seven qualitatively different ways of understanding essential knowledge for social education. The study indicates a professional practice-based theorisation of social education that justifies attention to discipline-based knowledge and teacher identity in the middle years.

Children’s rights in India : parents’ and teachers’ attitudes, knowledge and perceptions

Individuals’ attitudes influence their behaviour towards children, including whether children’s rights and welfare are promoted. The attitudes generally present in a society shape a culture of how children are perceived and treated. This study explored the attitudes and knowledge of 300 Indian parents and teachers regarding children’s rights, and their perceptions about whether selected rights were secured in reality. Findings revealed that most parents and teachers had positive attitudes about children’s rights, including rights to health and education, and freedom from child marriage and inappropriate work. Yet, about one quarter of participants did not think children should have the rights to freedom of expression and association. Knowledge of laws promoting children’s rights was poor. Most parents and teachers perceived a denial of seven key rights in Indian children’s lived experience. Overall, fijindings suggest a need to heighten awareness of children’s rights and needs, which can improve attitudes towards the treatment of children. Effforts to heighten awareness and attitudes towards children’s rights are needed across society and in key sectors to enhance children’s lived experience.

Eliciting Expert Knowledge in Conservation Science

Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge.

Visualising mathematical knowledge and understanding

Contemporary mathematics education attempts to instil within learners the conceptualization of mathematics as a highly organized and inter-connected set of ideas. To support this, a means to graphically represent this organization of ideas is presented which reflects the cognitive mechanisms that shape a learner’s understanding. This organisation of information may then be analysed, with the view to informing the design of mathematics instruction in face-to-face and/or computer-mediated learning environments. However, this analysis requires significant work to develop both theory and practice.

Proteomics science & society : the role of knowledge translation in moving towards clinical applications

Background: Outside the mass-spectrometer, proteomics research does not take place in a vacuum. It is affected by policies on funding and research infrastructure. Proteomics research both impacts and is impacted by potential clinical applications. It provides new techniques & clinically relevant findings, but the possibilities for such innovations (and thus the perception of the potential for the field by funders) are also impacted by regulatory practices and the readiness of the health sector to incorporate proteomics-related tools & findings. Key to this process is how knowledge is translated. Methods: We present preliminary results from a multi-year social science project, funded by the Canadian Institutes of Health Research, on the processes and motivations for knowledge translation in the health sciences. The proteomics case within this wider study uses qualitative methods to examine the interplay between proteomics science and regulatory and policy makers regarding clinical applications of proteomics. Results: Adopting an interactive format to encourage conference attendees’ feedback, our poster focuses on deficits in effective knowledge translation strategies from the laboratory to policy, clinical, & regulatory arenas. An analysis of the interviews conducted to date suggests five significant choke points: the changing priorities of funding agencies; the complexity of proteomics research; the organisation of proteomics research; the relationship of proteomics to genomics and other omics sciences; and conflict over the appropriate role of standardisation. Conclusion: We suggest that engagement with aspects of knowledge translation, such as those mentioned above, is crucially important for the eventual clinical application ofproteomics science on any meaningful scale.

An analytical tool that quantifies cellular morphology changes from three-dimensional fluorescence images

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology(1) even in complex tissue sections(2). Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells(3), however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.

Engagement, persistence, progress and success as theoretically distinct aspects of business creation processes

Starting from the vantage point that explaining success at creating a venture should be the unique contribution—or at least one unique contribution—of entrepreneurship research, we argue that this success construct has not yet been adequately defined an operationalized. We thus offer suggestions for more precise conceptualization and measurement of this central construct. Rather than regarding various success proxies used in prior research as poor operationalizations of success we argue that they represent other important aspects of the venture creation process: engagement, persistence and progress. We hold that in order to attain a better understanding of venture creation these constructs also need to be theoretically defined. Further, their respective drivers need to be theorized and tested separately. We suggest theoretical definitions of each. We then develop and test hypotheses concerning how human capital, venture idea novelty and business planning has different impact on the different assessments of the process represented by engagement, persistence, progress and success. The results largely confirm the stated hypotheses, suggesting that the conceptual and empirical approach we are suggesting is a path towards improved understanding of the central entrepreneurship phenomenon of new venture creation.

Maintaining a cognitive map in darkness : the need to fuse boundary knowledge with path integration

Spatial navigation requires the processing of complex, disparate and often ambiguous sensory data. The neurocomputations underpinning this vital ability remain poorly understood. Controversy remains as to whether multimodal sensory information must be combined into a unified representation, consistent with Tolman's "cognitive map", or whether differential activation of independent navigation modules suffice to explain observed navigation behaviour. Here we demonstrate that key neural correlates of spatial navigation in darkness cannot be explained if the path integration system acted independently of boundary (landmark) information. In vivo recordings demonstrate that the rodent head direction (HD) system becomes unstable within three minutes without vision. In contrast, rodents maintain stable place fields and grid fields for over half an hour without vision. Using a simple HD error model, we show analytically that idiothetic path integration (iPI) alone cannot be used to maintain any stable place representation beyond two to three minutes. We then use a measure of place stability based on information theoretic principles to prove that featureless boundaries alone cannot be used to improve localization above chance level. Having shown that neither iPI nor boundaries alone are sufficient, we then address the question of whether their combination is sufficient and - we conjecture - necessary to maintain place stability for prolonged periods without vision. We addressed this question in simulations and robot experiments using a navigation model comprising of a particle filter and boundary map. The model replicates published experimental results on place field and grid field stability without vision, and makes testable predictions including place field splitting and grid field rescaling if the true arena geometry differs from the acquired boundary map. We discuss our findings in light of current theories of animal navigation and neuronal computation, and elaborate on their implications and significance for the design, analysis and interpretation of experiments.