118 resultados para Knowledge Management Practice
Resumo:
Purpose: The aim of this article is to detail the correlation between quality management, specifically its tools and critical success factors, and performance in terms of primary operational and secondary organisational performances. Design/methodology/approach: Survey data from the UK and Turkey were analysed using exploratory factor analyses, structural equation modelling and regression analysis. Findings: The results show that quality management has a significant and positive impact on both primary and secondary performances; that Turkish and UK attitudes to quality management are similar; and that quality management is widely practised in manufacturing and service industries but has more statistical emphasis in the manufacturing sector. The main challenge for making quality management practice more effective lies in an appropriate balanced use of the different sorts of the tools and critical success factors. Originality/value: This study takes a novel approach by: (i) exploring the relationship between primary operational and secondary organisational performances, (ii) using service and manufacturing data and (iii) making a cross-country comparison between the UK (a developed economy) and Turkey (a developing economy). Limitations: Detailed contrast provided between only two countries. © 2013 Copyright Taylor and Francis Group, LLC.
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In this demonstration, we will present a semantic environment called the K-Box. The K-Box supports the lightweight integration of knowledge tools, with a focus on semantic tools, but with the flexibility to integrate natural language and conventional tools. We discuss the implementation of the framework, and two existing applications, including details of a new application for developers of semantic workflows. The demonstration will be of interest to developers and researchers of ontology-based knowledge management systems, and semantic desktops, and to analysts working with cross-media information. © 2011 ACM.
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In current organizations, valuable enterprise knowledge is often buried under rapidly expanding huge amount of unstructured information in the form of web pages, blogs, and other forms of human text communications. We present a novel unsupervised machine learning method called CORDER (COmmunity Relation Discovery by named Entity Recognition) to turn these unstructured data into structured information for knowledge management in these organizations. CORDER exploits named entity recognition and co-occurrence data to associate individuals in an organization with their expertise and associates. We discuss the problems associated with evaluating unsupervised learners and report our initial evaluation experiments in an expert evaluation, a quantitative benchmarking, and an application of CORDER in a social networking tool called BuddyFinder.
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The work reported in this paper is part of a project simulating maintenance operations in an automotive engine production facility. The decisions made by the people in charge of these operations form a crucial element of this simulation. Eliciting this knowledge is problematic. One approach is to use the simulation model as part of the knowledge elicitation process. This paper reports on the experience so far with using a simulation model to support knowledge management in this way. Issues are discussed regarding the data available, the use of the model, and the elicitation process itself.
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Despite much anecdotal and oftentimes empirical evidence that black and ethnic minority employees do not feel integrated into organisational life and the implications of this lack of integration for their career progression, there is a dearth of research on the nature of the relationship black and ethnic minority employees have with their employing organisations. Additionally, research examining the relationship between diversity management and work outcomes has returned mixed findings. Scholars have attributed this to the lack of an empirically validated measure of workforce diversity management. Accordingly, I sought to address these gaps in the extant literature in a two-part study grounded in social exchange theory. In Study 1, I developed and validated a measure of workforce diversity management practices. Data obtained from a sample of ethnic minority employees from a cross section of organisations provided support for the validity of the scale. In Study 2, I proposed and tested a social-exchange-based model of the relationship between black and ethnic minority employees’ and their employing organisations, as well as assessed the implications of this relationship for their work outcomes. Specifically, I hypothesised: (i) perception of support for diversity, perception of overall justice, and developmental experiences (indicators of integration into organisational life) as mediators of the relationship between diversity management and social exchange with organisation; (ii) the moderating influence of diversity climate on the relationship between diversity management and these indicators of integration; and (iii) the work outcomes of social exchange with organisation defined in terms of career satisfaction, turnover intention and strain. SEM results provide support for most of the hypothesised relationships. The findings of the study contribute to the literature on workforce diversity management in a number of ways. First, the development and validation of a diversity management practice scale constitutes a first step in resolving the difficulty in operationalising and measuring the diversity management construct. Second, it explicates how and why diversity management practices influence a social exchange relationship with an employing organisation, and the implications of this relationship for the work outcomes of black and ethnic minority employees. My study’s focus on employee work outcomes is an important corrective to the predominant focus on organisational-level outcomes of diversity management. Lastly, by focusing on ethno-racial diversity my research complements the extant research on such workforce diversity indicators as age and gender.
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The profusion of performance measurement models suggested by Management Accounting literature in the 1990’s is one illustration of the substantial changes in Management Accounting teaching materials since the publication of “Relevance Lost” in 1987. At the same time, in the general context of increasing competition and globalisation it is widely thought that national cultural differences are tending to disappear, meaning that management techniques used in large companies, including performance measurement and management instruments (PMS), tend to be the same, irrespective of the company nationality or location. North American management practice is traditionally described as a contractually based model, mainly focused on financial performance information and measures (FPMs), more shareholder-focused than French companies. Within France, literature historically defined performance as being broadly multidimensional, driven by the idea that there are no universal rules of management and that efficient management takes into account local culture and traditions. As opposed to their North American brethren, French companies are pressured more by the financial institutions that fund them rather than by capital markets. Therefore, they pay greater attention to the long-term because they are not subject to quarterly capital market objectives. Hence, management in France should rely more on long-term qualitative information, less financial, and more multidimensional data to assess performance than their North American counterparts. The objective of this research is to investigate whether large French and US companies’ practices have changed in the way the textbooks have changed with regards to performance measurement and management, or whether cultural differences are still driving differences in performance measurement and management between them. The research findings support the idea that large US and French companies share the same PMS features, influenced by ‘universal’ PM models.
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Purpose – This paper describes a “work in progress” research project being carried out with a public health care provider in the UK, a large NHS hospital Trust. Enhanced engagement with patients is one of the Trust’s core principles, but it is recognised that much more needs to be done to achieve this, and that ICT systems may be able to provide some support. The project is intended to find ways to better capture and evaluate the “voice of the patient” in order to lead to improvements in health care quality, safety and effectiveness. Design/methodology/approach – We propose to investigate the use of a patient-orientated knowledge management system (KMS) in managing knowledge about and from patients. The study is a mixed methods (quantitative and qualitative) investigation based on traditional action research, intended to answer the following three research questions: (1) How can a KMS be used as a mechanism to capture and evaluate patient experiences to provoke patient service change (2) How can the KMS assist in providing a mechanism for systematising patient engagement? (3) How can patient feedback be used to stimulate improvements in care, quality and safety? Originality/value –This methodology aims to involve patients at all phases of the study from its initial design onwards, thus leading to an understanding of the issues associated with using a KMS to manage knowledge about and for patients that is driven by the patients themselves. Practical implications – The outcomes of the project for the collaborating hospital will be firstly, a system for capturing and evaluating knowledge about and from patients, and then as a consequence, improved outcomes for both the patients and the service provider. More generally, it will produce a set of guidelines for managing patient knowledge in an NHS hospital that have been tested in one case example.
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This PhD thesis analyses networks of knowledge flows, focusing on the role of indirect ties in the knowledge transfer, knowledge accumulation and knowledge creation process. It extends and improves existing methods for mapping networks of knowledge flows in two different applications and contributes to two stream of research. To support the underlying idea of this thesis, which is finding an alternative method to rank indirect network ties to shed a new light on the dynamics of knowledge transfer, we apply Ordered Weighted Averaging (OWA) to two different network contexts. Knowledge flows in patent citation networks and a company supply chain network are analysed using Social Network Analysis (SNA) and the OWA operator. The OWA is used here for the first time (i) to rank indirect citations in patent networks, providing new insight into their role in transferring knowledge among network nodes; and to analyse a long chain of patent generations along 13 years; (ii) to rank indirect relations in a company supply chain network, to shed light on the role of indirectly connected individuals involved in the knowledge transfer and creation processes and to contribute to the literature on knowledge management in a supply chain. In doing so, indirect ties are measured and their role as means of knowledge transfer is shown. Thus, this thesis represents a first attempt to bridge the OWA and SNA fields and to show that the two methods can be used together to enrich the understanding of the role of indirectly connected nodes in a network. More specifically, the OWA scores enrich our understanding of knowledge evolution over time within complex networks. Future research can show the usefulness of OWA operator in different complex networks, such as the on-line social networks that consists of thousand of nodes.
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Ashby wrote about cybernetics, during which discourse he described a Law that attempts to resolve difficulties arising in complex situations – he suggested using variety to combat complexity. In this paper, we note that the delegates to the UN Framework Convention on Climate Change (UNFCCC) meeting in Kyoto, 1997, were offered a ‘simplifying solution’ to cope with the complexity of discussing multiple pollutants allegedly contributing to ‘climate change’. We assert that the adoption of CO2eq has resulted in imprecise thinking regarding the ‘carbon footprint’ – that is, ‘CO2’ – to the exclusion of other pollutants. We propose, as Ashby might have done, that the CO2eq and other factors within the ‘climate change’ negotiations be disaggregated to allow careful and specific individual solutions to be agreed on each factor. We propose a new permanent and transparent ‘action group’ be in charge of agenda setting and to manage the messy annual meetings. This body would be responsible for achieving accords at these annual meetings, rather than forcing this task on national hosts. We acknowledge the task is daunting and we recommend moving on from Ashby's Law to Beer's Viable Systems approach.
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In this paper we investigate the relation between knowledge and political action, focusing on knowledge claims stemming from science that at the same time have relevance in a policy context. In so doing, we will revisit some well-known and some lesser known approaches, such as C.P. Snow's thesis of the two cultures and Mannheim's conceptualization of theory and practice. We arrive at a distinction between knowledge for practice and practical knowledge, which we briefly apply to the case of climate change science and policy. We state as our thesis that policy is ever more reliant on knowledge, but science can deliver ever less certainty. Political decisions and programs have to recognize this fact, either implicitly or explicitly. This creates a paradox that is normally resolved through the political decision and not the dissemination of "truth" in the sense of uncontested knowledge. We use the case of the Intergovernmental Panel on Climate Change as an example. © 2012 Copyright ICCR Foundation.
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The sharing of near real-time traceability knowledge in supply chains plays a central role in coordinating business operations and is a key driver for their success. However before traceability datasets received from external partners can be integrated with datasets generated internally within an organisation, they need to be validated against information recorded for the physical goods received as well as against bespoke rules defined to ensure uniformity, consistency and completeness within the supply chain. In this paper, we present a knowledge driven framework for the runtime validation of critical constraints on incoming traceability datasets encapuslated as EPCIS event-based linked pedigrees. Our constraints are defined using SPARQL queries and SPIN rules. We present a novel validation architecture based on the integration of Apache Storm framework for real time, distributed computation with popular Semantic Web/Linked data libraries and exemplify our methodology on an abstraction of the pharmaceutical supply chain.
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Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.
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During group meetings it is often difficult for participants to effectively: share their knowledge to inform the outcome; acquire new knowledge from others to broaden and/or deepen their understanding; utilise all available knowledge to design an outcome; and record (to retain) the rationale behind the outcome to inform future activities. These are difficult because, for example: only one person can share knowledge at once which challenges effective sharing; information overload makes acquisition problematic and can marginalize important knowledge; and intense dialog of conflicting views makes recording more complex.