Virtual manufacturing:a study of some important issues relating to the transformation of traditional manufacturing organisations

This thesis starts with a literature review, outlining the major issues identified in the literature concerning virtual manufacturing enterprise (VME) transformation. Then it details the research methodology used – a systematic approach for empirical research. next, based on the conceptual framework proposed, this thesis builds three modules to form a reference model, with the purpose of clarifying the important issues relevant to transforming a traditional manufacturing company into a VME. The first module proposes a mechanism of VME transformation – operating along the VME metabolism. The second module builds a management function within a VME to ensure a proper operation of the mechanism. This function helps identify six areas as closely related to VME transformation: lean manufacturing; competency protection; internal operation performance measurement; alliance performance measurement; knowledge management; alliance decision making. The third module continues and proposes an alliance performance measurement system which includes 14 categories of performance indicators. An analysis template for alliance decision making is also proposed and integrated into the first module. To validate these three modules, 7 manufacturing organisations (5 in China and 2 in the UK) were investigated, and these field case studies are analysed in this thesis. The evidence found in these organisations, together with the evidence collected from the literature, including both researcher views and literature case studies, provide support for triangulation evidence. In addition, this thesis identifies the strength and weakness patterns of the manufacturing companies within the theoretical niche of this research, and clarifies the relationships among some major research areas from the perspective of virtual manufacturing. Finally, the research findings are summarised, as well as their theoretical and practical implications. Research limitations and recommendations for future work conclude this thesis.

A novel framework of training hidden Markov support vector machines from lightly-annotated data

Natural language understanding (NLU) aims to map sentences to their semantic mean representations. Statistical approaches to NLU normally require fully-annotated training data where each sentence is paired with its word-level semantic annotations. In this paper, we propose a novel learning framework which trains the Hidden Markov Support Vector Machines (HM-SVMs) without the use of expensive fully-annotated data. In particular, our learning approach takes as input a training set of sentences labeled with abstract semantic annotations encoding underlying embedded structural relations and automatically induces derivation rules that map sentences to their semantic meaning representations. The proposed approach has been tested on the DARPA Communicator Data and achieved 93.18% in F-measure, which outperforms the previously proposed approaches of training the hidden vector state model or conditional random fields from unaligned data, with a relative error reduction rate of 43.3% and 10.6% being achieved.

Knowledge mediation and overlapping in interfirm networks

Purpose – The literature on interfirm networks devotes scant attention to the ways collaborating firms combine and integrate the knowledge they share and to the subsequent learning outcomes. This study aims to investigate how motorsport companies use network ties to share and recombine knowledge and the learning that occurs both at the organizational and dyadic network levels. Design/methodology/approach – The paper adopts a qualitative and inductive approach with the aim of developing theory from an in-depth examination of the dyadic ties between motorsport companies and the way they share and recombine knowledge. Findings – The research shows that motorsport companies having substantial competences at managing knowledge flows do so by getting advantage of bridging ties. While bridging ties allow motorsport companies to reach distant and diverse sources of knowledge, their strengthening and the formation of relational capital facilitate the mediation and overlapping of that knowledge. Research limitations/implications – The analysis rests on a qualitative account in a single industry and does not take into account different types of inter-firm networks (e.g. alliances; constellations; consortia etc.) and governance structures. Cross-industry analyses may provide a more fine-grained picture of the practices used to recombine knowledge and the ideal composition of inter-firm ties. Practical implications – This study provides some interesting implications for scholars and managers concerned with the management of innovation activities at the interfirm level. From a managerial point of view, the recognition of the different roles played by network spanning connections is particularly salient and raises issues concerning the effective design and management of interfirm ties. Originality/value – Although much of the literature emphasizes the role of bridging ties in connecting to diverse pools of knowledge, this paper goes one step further and investigates in more depth how firms gather and combine distant and heterogeneous sources of knowledge through the use of strengthened bridging ties and a micro-context conducive to high quality relationships.

Filling knowledge gaps:knowledge sharing across inter-firm boundaries and occupational communities

This paper explores the micro-level processes of interaction across organisational boundaries and occupational communities. Based on a retrospective processual analysis, this study shows that in filling knowledge gaps, organisations put in place a series of knowledge mechanisms, which lead them to socially interact with their alliance partners. Both the deployment of existing knowledge and the creation of new knowledge are based on processes of interaction, which derive from the interplay between alliance actors. It is suggested that through both social interaction and the use of boundary objects, individuals are able to communicate, engage in problem-solving activities and share their ideas to fill knowledge gaps.

Changing career models and capacity for innovation in professional services

A number of professional sectors have recently moved away from their longstanding career model of up-or-out promotion and embraced innovative alternatives. Professional labor is a critical resource in professional service firms. Therefore, changes to these internal labor markets are likely to trigger other innovations, for example in knowledge management, incentive schemes and team composition. In this chapter we look at how new career models affect the core organizing model of professional firms and, in turn, their capacity for and processes of innovation. We consider how professional firms link the development of human capital and the division of professional labor to distinctive demands for innovation and how novel career systems help them respond to these demands.

The role of SHRM in turning tacit knowledge into explicit knowledge:a cross-national study of the UK and Malta

We propose that strategic human resource management (SHRM) practices nurture a context of knowledge sharing where tacit knowledge can be turned into explicit knowledge and that this type of knowledge sharing promotes innovative behaviours. We draw on the fields of knowledge management and international human resource management to show why organisations need to turn tacit knowledge into explicit knowledge to gain most from their workforce skills and creativity. Findings from a couple of cross-national case studies show how SHRM promotes employees to interact and share knowledge so that there is a conversion of tacit knowledge to explicit knowledge that informs innovative behaviour. In Case Study 1, the focus is on a UK local authority that implemented a bundle of SHRM practices through a people management programme, which resulted in a flattened management structure. In Case Study 2, the focus is on a geriatric hospital in Malta that introduced a management presence to an interdisciplinary team working to improve patient care. The analysis also highlights the methodological contribution of qualitative research for enabling inductive enquiry that yields emergent themes - an approach not typically seen in SHRM innovation studies. © 2013 Taylor & Francis.

A comprehensive solution to procedural knowledge acquisition using information extraction

Procedural knowledge is the knowledge required to perform certain tasks. It forms an important part of expertise, and is crucial for learning new tasks. This paper summarises existing work on procedural knowledge acquisition, and identifies two major challenges that remain to be solved in this field; namely, automating the acquisition process to tackle bottleneck in the formalization of procedural knowledge, and enabling machine understanding and manipulation of procedural knowledge. It is believed that recent advances in information extraction techniques can be applied compose a comprehensive solution to address these challenges. We identify specific tasks required to achieve the goal, and present detailed analyses of new research challenges and opportunities. It is expected that these analyses will interest researchers of various knowledge management tasks, particularly knowledge acquisition and capture.

An integrated environment for semantic knowledge work

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.

Ontology-based knowledge capture and sharing in enterprise organisations

Despite years of effort in building organisational taxonomies, the potential of ontologies to support knowledge management in complex technical domains is under-exploited. The authors of this chapter present an approach to using rich domain ontologies to support sense-making tasks associated with resolving mechanical issues. Using Semantic Web technologies, the authors have built a framework and a suite of tools which support the whole semantic knowledge lifecycle. These are presented by describing the process of issue resolution for a simulated investigation concerning failure of bicycle brakes. Foci of the work have included ensuring that semantic tasks fit in with users’ everyday tasks, to achieve user acceptability and support the flexibility required by communities of practice with differing local sub-domains, tasks, and terminology.

Relation discovery from web data for competency management

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.

Originator or propagator? Incorporating social role theory into topic models for twitter content analysis

A large number of studies have been devoted to modeling the contents and interactions between users on Twitter. In this paper, we propose a method inspired from Social Role Theory (SRT), which assumes that a user behaves differently in different roles in the generation process of Twitter content. We consider the two most distinctive social roles on Twitter: originator and propagator, who respectively posts original messages and retweets or forwards the messages from others. In addition, we also consider role-specific social interactions, especially implicit interactions between users who share some common interests. All the above elements are integrated into a novel regularized topic model. We evaluate the proposed method on real Twitter data. The results show that our method is more effective than the existing ones which do not distinguish social roles. Copyright 2013 ACM.

Using patient knowledge for better health systems

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.