Conceptualising social media support for tacit knowledge sharing: physicians’ perspectives and experiences

Purpose – This paper aims to explore the potential contributions of social media in supporting tacit knowledge sharing, according to the physicians’ perspectives and experiences. Design/methodology/approach – Adopting a qualitative survey design, 24 physicians were interviewed. Purposive and snowball sampling were used to select the participants. Thematic analysis approach was used for data analysis. Findings – The study revealed five major themes and over 20 sub-themes as potential contributions of social media to tacit knowledge flow among physicians. The themes included socialising, practising, networking, storytelling and encountering. In addition, with the help of the literature and the supporting data, the study proposed a conceptual model that explains the potential contribution of social media to tacit knowledge sharing. Research limitations/implications – The study had both theoretical (the difficulty of distinguishing tacit and explicit knowledge in practice) and practical limitations (small sample size). The study findings have implications for the healthcare industry whose clinical teams are not always physically co-located but must exchange their critical experiential and tacit knowledge. Originality/value – The study has opened up a new discussion of this area by demonstrating and conceptualising how social media tools may facilitate tacit knowledge sharing.

The role of organisational culture, trust and mechanisms in inter-project knowledge sharing

Knowledge has been recognised as a powerful yet intangible asset, which is difficult to manage. This is especially true in a project environment where there is the potential to repeat mistakes, rather than learn from previous experiences. The literature in the project management field has recognised the importance of knowledge sharing (KS) within and between projects. However, studies in that field focus primarily on KS mechanisms including lessons learned (LL) and post project reviews as the source of knowledge for future projects, and only some preliminary research has been carried out on the aspects of project management offices (PMOs) and organisational culture (OC) in KS. This study undertook to investigate KS behaviours in an inter-project context, with a particular emphasis on the role of trust, OC and a range of knowledge sharing mechanisms (KSM) in achieving successful inter-project knowledge sharing (I-PKS). An extensive literature search resulted in the development of an I-PKS Framework, which defined the scope of the research and shaped its initial design. The literature review indicated that existing research relating to the three factors of OC, trust and KSM remains inadequate in its ability to fully explain the role of these contextual factors. In particular, the literature review identified these areas of interest: (1) the conflicting answers to some of the major questions related to KSM, (2) the limited empirical research on the role of different trust dimensions, (3) limited empirical evidence of the role of OC in KS, and (4) the insufficient research on KS in an inter-project context. The resulting Framework comprised the three main factors including: OC, trust and KSM, demonstrating a more integrated view of KS in the inter-project context. Accordingly, the aim of this research was to examine the relationships between these three factors and KS by investigating behaviours related to KS from the project managers‘ (PMs‘) perspective. In order to achieve the aim, this research sought to answer the following research questions: 1. How does organisational culture influence inter-project knowledge sharing? 2. How does the existence of three forms of trust — (i) ability, (ii) benevolence and (iii) integrity — influence inter-project knowledge sharing? 3. How can different knowledge sharing mechanisms (relational, project management tools and process, and technology) improve inter-project knowledge sharing behaviours? 4. How do the relationships between these three factors of organisational culture, trust and knowledge sharing mechanisms improve inter-project knowledge sharing? a. What are the relationships between the factors? b. What is the best fit for given cases to ensure more effective inter-project knowledge sharing? Using multiple case studies, this research was designed to build propositions emerging from cross-case data analysis. The four cases were chosen on the basis of theoretical sampling. All cases were large project-based organisations (PBOs), with a strong matrix-type structure, as per the typology proposed by the Project Management Body of Knowledge (PMBoK) (2008). Data were collected from project management departments of the respective organisations. A range of analytical techniques were used to deal with the data including pattern matching logic and explanation building analysis, complemented by the use of NVivo for data coding and management. Propositions generated at the end of the analyses were further compared with the extant literature, and practical implications based on the data and literature were suggested in order to improve I-PKS. Findings from this research conclude that OC, trust, and KSM contribute to inter-project knowledge sharing, and suggest the existence of relationships between these factors. In view of that, this research identified the relationships between different trust dimensions, suggesting that integrity trust reinforces the relationship between ability trust and knowledge sharing. Furthermore, this research demonstrated that characteristics of culture and trust interact to reinforce preferences for mechanisms of knowledge sharing. This means that cultures that facilitate characteristics of Clan type are more likely to result in trusting relationships, hence are more likely to use organic sources of knowledge for both tacit and explicit knowledge exchange. In contrast, cultures that are empirically driven, based on control, efficiency, and measures (characteristics of Hierarchy and Market types) display tendency to develop trust primarily in ability of non-organic sources, and therefore use these sources to share mainly explicit knowledge. This thesis contributes to the project management literature by providing a more integrative view of I-PKS, bringing the factors of OC, trust and KSM into the picture. A further contribution is related to the use of collaborative tools as a substitute for static LL databases and as a facilitator for tacit KS between geographically dispersed projects. This research adds to the literature on OC by providing rich empirical evidence of the relationships between OC and the willingness to share knowledge, and by providing empirical evidence that OC has an effect on trust; in doing so this research extends the theoretical propositions outlined by previous research. This study also extends the research on trust by identifying the relationships between different trust dimensions, suggesting that integrity trust reinforces the relationship between ability trust and KS. Finally, this research provides some directions for future studies.

The strategic importance of tacit knowledge management activities in construction

Purpose: Tacit knowledge is perceived as the most strategically important resource of the construction organisation, and the only renewable and sustainable base for its activities and competitiveness. Knowledge management (KM) activities that deal with tacit knowledge are essential in helping an organisation to achieve its long-term organisational objectives. The purpose of this paper is to provide empirical evidence for the stronger strategic role of tacit KM in comparison to explicit KM. Design/methodology/approach: A questionnaire survey was administered in 2005 to a sample of construction contractors operating in Hong Kong to elicit opinions on the internal business environment, intensity of KM activities as executed by targeted organisations, and contribution of these activities to business performance (BP). A total of 149 usable responses were received from 99 organisations representing about 38 per cent of the sampling frame. The statistical analyses helped to map the reported KM activities into two groups that, respectively, deal with tacit and explicit knowledge. The sensitivity to variations of organisational policies and strength of association with BP in relation to the two groups of KM activities were also compared empirically. A total of 15 interviews with the managerial and professional staff of leading contractors was undertaken to provide insightful narratives of KM implementations. Findings: The effective implementation of organisational policies, such as encouraging innovations and strengthening strategic guidance for KM, would facilitate human interactions of tacit KM. Higher intensity of activities in managing tacit knowledge would ultimately help the organisations to achieve economic gain in the long run. Originality/value: The stronger strategic role of tacit KM is empirically investigated and established within the context of construction organisations.

The Innovation Management Program (IMP) : a holistic approach to managing change in knowledge based firms

Innovation Management (IM) in most knowledge based firms is used on an adhoc basis where senior managers use this term to leverage competitive edge without understanding its true meaning and how its robust application in organisation impacts organisational performance. There have been attempts in the manufacturing industry to harness the innovative potential of the business and apprehend its use as a point of difference to improve financial and non financial outcomes. However further work is required to innovatively extrapolate the lessons learnt to introduce incremental and/or radical innovation to knowledge based firms. An international structural engineering firm has been proactive in exploring and implementing this idea and has forged an alliance with the Queensland University of Technology to start the Innovation Management Program (IMP). The aim was to develop a permanent and sustainable program with which innovation can be woven through the fabric of the organisation. There was an intention to reinforce the firms’ vision and reinvigorate ideas and create new options that help in its realisation. This paper outlines the need for innovation in knowledge based firms and how this consulting engineering firm reacted to this exigency. The development of the Innovation Management Program, its different themes (and associated projects) and how they integrate to form a holistic model is also discussed. The model is designed around the need of providing professional qualification improvement opportunities for staff, setting-up organised, structured & easily accessible knowledge repositories to capture tacit and explicit knowledge and implement efficient project management strategies with a view to enhance client satisfaction. A Delphi type workshop is used to confirm the themes and projects. Some of the individual projects and their expected outcomes are also discussed. A questionnaire and interviews were used to collect data to select appropriate candidates responsible for leading these projects. Following an in-depth analysis of preliminary research results, some recommendations on the selection process will also be presented.

Using Enterprise 2.0 tools to facilitate knowledge transfer in complex engineering environments

An essential challenge for organizations wishing to overcome informational silos is to implement mechanisms that facilitate, encourage and sustain interactions between otherwise disconnected groups. Using three case examples, this paper explores how Enterprise 2.0 technologies achieve such goals, allowing for the transfer of knowledge by tapping into the tacit and explicit knowledge of disparate groups in complex engineering organizations. The paper is intended to be a timely introduction to the benefits and issues associated with the use of Enterprise 2.0 technologies with the aim of achieving the positive outcomes associated with knowledge management

Using social media to facilitate knowledge transfer in complex engineering environments : a primer for educators

While highly cohesive groups are potentially advantageous they are also often correlated with the emergence of knowledge and information silos based around those same functional or occupational clusters. Consequently, an essential challenge for engineering organisations wishing to overcome informational silos is to implement mechanisms that facilitate, encourage and sustain interactions between otherwise disconnected groups. This paper acts as a primer for those seeking to gain an understanding of the design, functionality and utility of a suite of software tools generically termed social media technologies in the context of optimising the management of tacit engineering knowledge. Underpinned by knowledge management theory and using detailed case examples, this paper explores how social media technologies achieve such goals, allowing for the transfer of knowledge by tapping into the tacit and explicit knowledge of disparate groups in complex engineering environments.

Australian national survey: preliminary findings

The National survey was the third phase in an ongoing initiative to identify critical success factors in ICT mediated supply chains. This study has been designed to harness the tacit and explicit knowledge to be found on the subject from the widest range of appropriate sources. At its core is the assumption that, provided with the fullest list of candidate success factors, a representative sample of experienced industry-based practitioners will (with the aid of statistical analysis) reveal a set of critical success factors. A postal survey has been judged to be the most appropriate mechanism for achieving this outcome.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Documenting reproduction and inequality : revisiting Jean Anyon’s “Social class and school knowledge”

Jean Anyon’s (1981) “Social class and school knowledge” was a landmark work in North American educational research. It provided a richly detailed qualitative description of differential, social-class-based constructions of knowledge and epistemological stance. This essay situates Anyon’s work in two parallel traditions of critical educational research: the sociology of the curriculum and classroom interaction and discourse analysis. It argues for the renewed importance of both quantitative and qualitative research on social reproduction and equity in the current policy context.

Chasing Reporters : Intertextuality, Entertainment and Public Knowledge

This paper examines ‘What Have We Learned From Current Affairs This Week?’: a very successful weekly segment from the ABC program The Chaser’s War on Everything. It argues that through its intertextual satire, this regular segment acts not as a traditional news program would in presenting news updates on current events, but as a text which reflects on the way news is reported and how this, in turn, may shape public discourse. While the program has been highly controversial (enduring many a loud call for it to be pulled from air), this form of light entertainment can play an important public service by encouraging citizens to ‘read through’ (Gray, 2006: 104) commercial current affairs’ façade of ‘quality’ journalism.

Urban, regional, national and global knowledge capital [Guest editorial]

Purpose – The purpose of this paper is to introduce the JKM 2010 annual special issue on knowledge based development (KBD) with reference to the multi-level analysis characteristic of the field. ----- ----- Design/methodology/approach – A description of the knowledge management approach at ESOC (European Space Operations Centre of the European Space Agency) is provided first. At the core of this approach is the breakdown of knowledge in individual technical domains followed by coverage analysis and criticality assessment. Such a framework becomes the reference for best knowledge acquisition, transfer and storage locus identification and subsequent knowledge management practices and guidelines. ----- ----- Findings – KBD provides an integrated framework to account for multidisciplinary analyses and multilevel practices in knowledge capital generation, distribution and utilization. ----- ----- Originality/value – The collection of papers included in the annual special issue on KBD provides a representative, composite view of the research topics and applications concerns in the field. Involving a number of disciplines and levels of analysis, issues ranging from the technological gatekeeper to global knowledge flows show the interdependence of KBD concepts and tools.

Improving matching process in social network using implicit and explicit user information

Personalised social matching systems can be seen as recommender systems that recommend people to others in the social networks. However, with the rapid growth of users in social networks and the information that a social matching system requires about the users, recommender system techniques have become insufficiently adept at matching users in social networks. This paper presents a hybrid social matching system that takes advantage of both collaborative and content-based concepts of recommendation. The clustering technique is used to reduce the number of users that the matching system needs to consider and to overcome other problems from which social matching systems suffer, such as cold start problem due to the absence of implicit information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased, using both user information (explicit data) and user behavior (implicit data).