Knowledge governance in project-based organizations : theoretical and empirical approaches

This paper conceptualizes knowledge governance (KG) in project-based organizations (PBOs) and its methodological approaches for empirical investigation. Three key contributions towards a multi-faceted view of KG and an understanding of KG in PBOs are advanced. These contributions include a definition of KG in PBOs, a conceptual framework to investigate KG and a methodological framework for empirical inquiry into KG in PBO settings. Our definition highlights the contingent nature of KG processes in relation to their organizational context. The conceptual framework addresses macro- and micro-level elements of KG and their interaction. The methodological framework proposes five different research approaches, structured by differentiation and integration of various ontological and epistemological stances. Together these contributions provide a novel platform for understanding KG in PBOs and developing new insights into the design and execution of research on KG within PBOs.

Modeling the viability of the free-ranging cheetah population in Namibia : an object-oriented Bayesian network approach

Conservation of free-ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Identifying the most important factors, making sense of various (and sometimes contrasting) findings, and taking decisions when little or no empirical data is available, are everyday challenges facing conservationists. Bayesian networks (BN) provide a statistical modeling framework that enables analysis and integration of information addressing different aspects of conservation. There has been an increased interest in the use of BNs to model conservation issues, however the development of more sophisticated BNs, utilizing object-oriented (OO) features, is still at the frontier of ecological research. We describe an integrated, parallel modeling process followed during a BN modeling workshop held in Namibia to combine expert knowledge and data about free-ranging cheetahs. The aim of the workshop was to obtain a more comprehensive view of the current viability of the free-ranging cheetah population in Namibia, and to predict the effect different scenarios may have on the future viability of this free-ranging cheetah population. Furthermore, a complementary aim was to identify influential parameters of the model to more effectively target those parameters having the greatest impact on population viability. The BN was developed by aggregating diverse perspectives from local and independent scientists, agents from the national ministry, conservation agency members and local fieldworkers. This integrated BN approach facilitates OO modeling in a multi-expert context which lends itself to a series of integrated, yet independent, subnetworks describing different scientific and management components. We created three subnetworks in parallel: a biological, ecological and human factors network, which were then combined to create a complete representation of free-ranging cheetah population viability. Such OOBNs have widespread relevance to the effective and targeted conservation management of vulnerable and endangered species.

A Bayesian network approach to modelling temporal behaviour of Lyngbya majuscula bloom initiation

Lyngbya majuscula is a cyanobacterium (blue-green algae) occurring naturally in tropical and subtropical coastal areas worldwide. Deception Bay, in Northern Moreton Bay, Queensland, has a history of Lyngbya blooms, and forms a case study for this investigation. The South East Queensland (SEQ) Healthy Waterways Partnership, collaboration between government, industry, research and the community, was formed to address issues affecting the health of the river catchments and waterways of South East Queensland. The Partnership coordinated the Lyngbya Research and Management Program (2005-2007) which culminated in a Coastal Algal Blooms (CAB) Action Plan for harmful and nuisance algal blooms, such as Lyngbya majuscula. This first phase of the project was predominantly of a scientific nature and also facilitated the collection of additional data to better understand Lyngbya blooms. The second phase of this project, SEQ Healthy Waterways Strategy 2007-2012, is now underway to implement the CAB Action Plan and as such is more management focussed. As part of the first phase of the project, a Science model for the initiation of a Lyngbya bloom was built using Bayesian Networks (BN). The structure of the Science Bayesian Network was built by the Lyngbya Science Working Group (LSWG) which was drawn from diverse disciplines. The BN was then quantified with annual data and expert knowledge. Scenario testing confirmed the expected temporal nature of bloom initiation and it was recommended that the next version of the BN be extended to take this into account. Elicitation for this BN thus occurred at three levels: design, quantification and verification. The first level involved construction of the conceptual model itself, definition of the nodes within the model and identification of sources of information to quantify the nodes. The second level included elicitation of expert opinion and representation of this information in a form suitable for inclusion in the BN. The third and final level concerned the specification of scenarios used to verify the model. The second phase of the project provides the opportunity to update the network with the newly collected detailed data obtained during the previous phase of the project. Specifically the temporal nature of Lyngbya blooms is of interest. Management efforts need to be directed to the most vulnerable periods to bloom initiation in the Bay. To model the temporal aspects of Lyngbya we are using Object Oriented Bayesian networks (OOBN) to create ‘time slices’ for each of the periods of interest during the summer. OOBNs provide a framework to simplify knowledge representation and facilitate reuse of nodes and network fragments. An OOBN is more hierarchical than a traditional BN with any sub-network able to contain other sub-networks. Connectivity between OOBNs is an important feature and allows information flow between the time slices. This study demonstrates more sophisticated use of expert information within Bayesian networks, which combine expert knowledge with data (categorized using expert-defined thresholds) within an expert-defined model structure. Based on the results from the verification process the experts are able to target areas requiring greater precision and those exhibiting temporal behaviour. The time slices incorporate the data for that time period for each of the temporal nodes (instead of using the annual data from the previous static Science BN) and include lag effects to allow the effect from one time slice to flow to the next time slice. We demonstrate a concurrent steady increase in the probability of initiation of a Lyngbya bloom and conclude that the inclusion of temporal aspects in the BN model is consistent with the perceptions of Lyngbya behaviour held by the stakeholders. This extended model provides a more accurate representation of the increased risk of algal blooms in the summer months and show that the opinions elicited to inform a static BN can be readily extended to a dynamic OOBN, providing more comprehensive information for decision makers.

Enhancing enterprise social network use : a control theory study

Organizations employ Enterprise Social Networks (ESNs) (e.g., Yammer) expecting better intra-organizational communication, effective knowledge sharing and, in general, greater collaboration. Despite their similarities with Public Social Networks (PSNs) (e.g., Twitter), ESNs are struggling to gain credence with employees. This paper is part of a larger research project that investigates mechanisms to enhance employees’ engagement in the ESNs. Through the lens of Control Theory, this paper reports preliminary findings of a pilot case study aimed to propose formal and informal mechanisms that impact employees’ intrinsic and extrinsic motivations to encourage their use of ESNs. The study results highlight (i) the need to better understand employees’ extrinsic and intrinsic motivations to use Social Networks, and (ii) that unlike a PSN which acts as a hedonic system, an ESN acts as a utilitarian system, highlighting the importance of supporting intrinsic motivations in its implementation.

Australian Diabetes Foot Network : practical guideline on the provision of footwear for people with diabetes

Trauma, in the form of pressure and/or friction from footwear, is a common cause of foot ulceration in people with diabetes. These practical recommendations regarding the provision of footwear for people with diabetes were agreed upon following review of existing position statements and clinical guidelines. The aim of this process was not to re-invent existing guidelines but to provide practical guidance for health professionals on how they can best deliver these recommendations within the Australian health system. Where information was lacking or inconsistent, a consensus was reached following discussion by all authors. Appropriately prescribed footwear, used alone or in conjunction with custom-made foot orthoses, can reduce pedal pressures and reduce the risk of foot ulceration. It is important for all health professionals involved in the care of people with diabetes to both assess and make recommendations on the footwear needs of their clients or to refer to health professionals with such skills and knowledge. Individuals with more complex footwear needs (for example those who require custom-made medical grade footwear and orthoses) should be referred to health professionals with experience in the prescription of these modalities and who are able to provide appropriate and timely follow-up. Where financial disadvantage is a barrier to individuals acquiring appropriate footwear, health care professionals should be aware of state and territory based equipment funding schemes that can provide financial assistance. Aboriginal and Torres Strait Islanders and people living in rural and remote areas are likely to have limited access to a broad range of footwear. Provision of appropriate footwear to people with diabetes in these communities needs be addressed as part of a comprehensive national strategy to reduce the burden of diabetes and its complications on the health system.

A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

Pipeline renewal decision support : a case study using LinEAR in a water pipeline network

This paper presents a case study for the application of a Linear Engineering Asset Renewal decision support software tool (LinEAR) at a water distribution network in Australia. This case study examines how the LinEAR can assist water utilities to minimise their total pipeline management cost, to make a long-term budget based on mathematically predicted expenditure, and to present calculated evidence for supporting their expenditure requirements. The outcomes from the study on pipeline renewal decision support demonstrate that LinEAR can help water utilities to improve the decision process and save renewal costs over a long-term by providing an optimum renewal schedules. This software can help organisation to accumulate technical knowledge and prediction future impact of the decision using what-if analysis.

Industry based rehabilitation and closure knowledge management system : scoping study

The Central Queensland Mine Rehabilitation Group (CQMRG) has hosted mine site rehabilitation inspections combined with technical workshops for more than 20 years. It was recognised at CQMRG's anniversary meeting in April 2013 that the vast body of knowledge held by rehabilitation and closure planning practitioners was being lost as senior rehabilitation experts retire from the industry. It was noted that even more knowledge could be readily lost unless a knowledge management platform was developed to capture, store and enable retrieval of this information. This loss of knowledge results in a significant cost to industry. This project was therefore undertaken to review tools which have the capability to gather the less formal knowledge as well as to make links to existing resources and bibliographic material. This scoping study evaluated eight alternative knowledge management systems to provide guidance on the best method of providing the industry with an up-to-date, good practice, knowledge management system for rehabilitation and closure practices, with capability for information sharing via a portal and discussion forum. This project provides guidance for a larger project which will implement the knowledge management system to meet the requirements of the CQMRG and be transferrable to other regions if applicable. It will also provide the opportunity to identify missing links between existing tools and their application. That is, users may not be aware of how these existing tools can be used to assist with mine rehabilitation planning and implementation and the development of a new platform will help to create those linkages. The outcomes of this project are directed toward providing access to a live repository of rehabilitation practice information which is Central Queensland coal mine-specific, namely: highlighting best practice activities, results of trials and innovative practices; updated legislative requirements; links to practices elsewhere; and informal anecdotal information relevant to particular sites which may be of assistance in the development of rehabilitation of new areas. Solutions to the rehabilitation of challenging spoils/soils will also be provided. The project will also develop a process which can be applied more broadly within the mining sector to other regions and other commodities. Providing a platform for uploading information and holding discussion forums which can be managed by a regional practitioner network enables the new system to be kept alive, driven by users and information needs as they evolve over time. Similar internet-based platforms exist and are managed successfully. The preferred knowledge management system will capture the less formal and more difficult to access knowledge from rehabilitation and mine closure practitioners and stakeholders through the CQMRG and other contributors. It will also provide direct links, and greater accessibility, to more formal sources of knowledge with anticipated cost savings to the industry and improved rehabilitation practices with successful transitioning to closure and post-mining land use.

Association hierarchy mining and its application for network traffic characterisation

This thesis presents an association rule mining approach, association hierarchy mining (AHM). Different to the traditional two-step bottom-up rule mining, AHM adopts one-step top-down rule mining strategy to improve the efficiency and effectiveness of mining association rules from datasets. The thesis also presents a novel approach to evaluate the quality of knowledge discovered by AHM, which focuses on evaluating information difference between the discovered knowledge and the original datasets. Experiments performed on the real application, characterizing network traffic behaviour, have shown that AHM achieves encouraging performance.

Application of a Bayesian Network complex system model to a successful community electricity demand reduction program

Utilities worldwide are focused on supplying peak electricity demand reliably and cost effectively, requiring a thorough understanding of all the factors influencing residential electricity use at peak times. An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008, and by 2011, peak demand had decreased to below pre-intervention levels. This paper applied field data discovered through qualitative in-depth interviews of 22 residential households at the community to a Bayesian Network complex system model to examine whether the system model could explain successful peak demand reduction in the case study location. The knowledge and understanding acquired through insights into the major influential factors and the potential impact of changes to these factors on peak demand would underpin demand reduction intervention strategies for a wider target group.

An international benchmark for the Australian OHS Body of Knowledge (BoK)

Benchmarking was used to compare the Australian SIA’s (Safety Institute of Australia) OHS BoK with three different approaches to systemize the knowledge that should be taught by universities. The Australian Health and Safety Professionals Alliance (HaSPA) Core Body of Knowledge for Generalist OHS Professionals was benchmarked against three other international bodies of knowledge, the German Ergonomic Society’s Body of Knowledge Ergonomics – Core Definition, Object Catalogue and Research Domains, the IEEE Computer Society Software Engineering Body of Knowledge and the American ‘Association of Schools of Public Health’ Master’s Degree in Public Health Core Competency Model. It was found that quality, structure and content of the OHS BoK ranked lowest when compared with the other benchmarked documents. The HaSPA body of knowledge was ranked poorly when compared to the German Ergonomic Society’s Body of Knowledge for Ergonomics, IEEE Computer Society Software Engineering Body of Knowledge and the American Association of Schools of Public Health Core Competency Model. Analysis and discussion of the HaSPA BoK is important given its use as an audit tool for tertiary education in Australia. Furthermore the International Network of Safety & Health Practitioner Organisations (INSHPO) is apparently promoting the Australian SIA’s OHS BoK as the basis of an international standard.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

Development and feasibility testing of an education program to improve knowledge and self-care among Aboriginal and Torres Strait Islander patients with heart failure

Background/Aim There is a 70% higher age-adjusted incidence of heart failure (HF) amongst Aboriginal and Torres Strait Islander people, three times more hospitalisations and twice as many deaths than non-Aboriginal people. There is a need to develop holistic yet individualised approaches in accord with the values of Aboriginal community healthcare to support patient education and self-care. The aim of this study was to re-design an existing HF educational resource (Fluid Watchers-Pacific Rim©) to be culturally safe for Aboriginal and Torres Strait Islander peoples, working in collaboration with the local community, and to conduct feasibility testing. Methods This study was conducted in two phases and utilised a mixed methods approach (qualitative and quantitative). Phase 1 of this study used action research methods to develop a culturally safe electronic resource to be provided to Aboriginal HF patients via a tablet computer. A HF expert panel adapted the existing resource to ensure it was evidence-based and contained appropriate language and images that reflects Aboriginal culture. A stakeholder group (which included Aboriginal workers and HF patients, as well as researchers and clinicians) then reviewed the resources and changes were made accordingly. In Phase 2, the new resource was tested on a sample of Aboriginal HF patients to assess feasibility and acceptability. Patient knowledge, satisfaction and self-care behaviours were measured using a before and after design with validated questionnaires. As this was a pilot test to determine feasibility, no statistical comparisons were made. Results - Phase 1: Throughout the process of resource development, two main themes emerged from the stakeholder consultation. These were the importance of identity, meaning that it was important to ensure that the resource accurately reflected the local community, with the appropriate clothing, skin tone and voice. The resource was adapted to reflect this and of the local community voiced the recordings for the resource. The other theme was comprehension; images were important and all text was converted to the first person and used plain language. - Phase 2: Five Aboriginal participants, mean age 61.6 ± 10.0 years, with NYHA Class III and IV heart failure were enrolled. Participants reported a high level of satisfaction with the resource (83.0%). HF knowledge (percentage of correct responses) increased from 48.0 ± 6.7% to 58.0 ± 9.7%, a 20.8% increase and results of the self-care index indicated that the biggest change was in patient confidence for self-care with a 95% increase in confidence score (46.7 ± 16.0 to 91.1 ± 11.5). Changes in management and maintenance scores varied between9275 patients. Conclusion By working in collaboration with HF experts, Aboriginal researchers and patients, a culturally safe HF resource has been developed for Aboriginal and Torres Strait Islander patients. Engaging Aboriginal researchers, capacity-building, and being responsive to local systems and structures enabled this pilot study to be successfully completed with the Aboriginal community and positive participant feedback demonstrated that the methodology used in this study was appropriate and acceptable; participants were able to engage with willingness and confidence.