An investigation of SMEs’ inter-organisational knowledge transfer needs in Internet marketing

Internet marketing, as a key area of e-commerce, plays an important role in SMEs’ e-commerce success. It is the use of Internet technologies in facilitating and supporting marketing activities. Its implementation and success require expert knowledge and extensive experience. SMEs admit that they are willing to embrace Internet marketing to enhance their business competitiveness, but do not know where to start and suffer from a lack of guidance. Evidence suggests that Internet marketing analysis is one of the most needed areas of training in e-commerce for SMEs. It is therefore evident that SMEs need to acquire Internet marketing knowledge from external sources. However, the majority of the literature fails to study what specific knowledge they need and from whom they should acquire the knowledge. This paper has addressed these issues through a questionnaire survey of UK SMEs in the service sector. It identifies SMEs’ specific transfer needs for Internet marketing knowledge, and discusses strategic issues for improving SMEs’ effectiveness of leveraging knowledge.

People, technology, processes and risk knowledge sharing

The present global economic crisis creates doubts about the good use of accumulated experience and knowledge in managing risk in financial services. Typically, risk management practice does not use knowledge management (KM) to improve and to develop new answers to the threats. A key reason is that it is not clear how to break down the “organizational silos” view of risk management (RM) that is commonly taken. As a result, there has been relatively little work on finding the relationships between RM and KM. We have been doing research for the last couple of years on the identification of relationships between these two disciplines. At ECKM 2007 we presented a general review of the literature(s) and some hypotheses for starting research on KM and its relationship to the perceived value of enterprise risk management. This article presents findings based on our preliminary analyses, concentrating on those factors affecting the perceived quality of risk knowledge sharing. These come from a questionnaire survey of RM employees in organisations in the financial services sector, which yielded 121 responses. We have included five explanatory variables for the perceived quality of risk knowledge sharing. These comprised two variables relating to people (organizational capacity for work coordination and perceived quality of communication among groups), one relating to process (perceived quality of risk control) and two related to technology (web channel functionality and RM information system functionality). Our findings so far are that four of these five variables have a significant positive association with the perceived quality of risk knowledge sharing: contrary to expectations, web channel functionality did not have a significant association. Indeed, in some of our exploratory regression studies its coefficient (although not significant) was negative. In stepwise regression, the variable organizational capacity for work coordination accounted for by far the largest part of the variation in the dependent variable perceived quality of risk knowledge sharing. The “people” variables thus appear to have the greatest influence on the perceived quality of risk knowledge sharing, even in a sector that relies heavily on technology and on quantitative approaches to decision making. We have also found similar results with the dependent variable perceived value of Enterprise Risk Management (ERM) implementation.

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.

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.

Knowledge elicitation supported by simulation

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.