The impact of unique characteristics of projects and project-based organisations on knowledge transfer

Knowledge has been recognised as an important organisational asset that increases in value when shared; the opposite to other organisational assets which decrease in value during their exploitation. Effective knowledge transfer in organisations helps to achieve and maintain competitive advantage and ultimately organisational success. So far, the research on knowledge transfer has focused on traditional (functional) organisations. Only recently has attention been directed towards knowledge transfer in projects. Existing research on project learning has recognised the need for knowledge transfer within and across projects in project-based organisations (PBOs). Most projects can provide valuable new knowledge from unexpected actions, approaches or problems experienced during the project phases. The aim of this paper is to demonstrate the impact of unique projects characteristics on knowledge transfer in PBO. This is accomplished through review of the literature and a series of interviews with senior project practitioners. The interviews complement the findings from the literature. Knowledge transfer in projects occurs by social communication and transfer of lessons learned where project management offices (PMOs) and project managers play significant roles in enhancing knowledge transfer and communication within the PBO and across projects. They act as connectors between projects and the PBO ‘hub’. Moreover, some project management processes naturally facilitate knowledge transfer across projects. On the other hand, PBOs face communication challenges due to unique and temporary characteristics of projects. The distance between projects and the lack or weakness of formal links across projects, create communication problems that impede knowledge transfer across projects. The main contribution of this paper is to demonstrate that both social communication and explicit informational channels play important role in inter-project knowledge transfer. Interviews also revealed the important role organisational culture play in knowledge transfer in PBOs.

Development of a Rep-inducible, BBTV-based expression system in banana

Banana bunchy top is regarded as the most important viral disease of banana, causing significant yield losses worldwide. The disease is caused by Banana bunchy top virus (BBTV), which is a circular ssDNA virus belonging to the genus Babuvirus in the family Nanoviridae. There are currently few effective control strategies for this and other ssDNA viruses. “In Plant Activation” (InPAct) is a novel technology being developed at QUT for ssDNA virus-activated suicide gene expression. The technology exploits the rolling circle replication mechanism of ssDNA viruses and is based on a unique “split” gene design such that suicide gene expression is only activated in the presence of the viral Rep. This PhD project aimed to develop a BBTV-based InPAct system as a suicide gene strategy to control BBTV. The BBTV-based InPAct vector design requires a BBTV intergenic region (IR) to be embedded within an intron in the gene expression cassette. To ensure that the BBTV IR would not interfere with intron splicing, a TEST vector was initially generated that contained the entire BBTV IR embedded within an intron in a β-glucuronidase (GUS) expression vector. Transient GUS assays in banana embryogenic cell suspensions indicated that cryptic intron splice sites were present within the IR. Transcript analysis revealed two cryptic intron splice sites in the Domain III sequence of the CR-M within the IR. Removal of the CR-M from the TEST vector resulted in an enhancement of GUS expression suggesting that the cryptic intron splice sites had been removed. An InPAct GUS vector was subsequently generated that contained the modified BBTV IR, with the CR-M (minus Domain III) repositioned within the InPAct cassette. Using transient histochemical and fluorometric GUS assays in banana embryogenic cells, the InPAct GUS vector was shown to be activated in the presence of the BBTV Rep. However, the presence of both BBTV Rep and Clink was shown to have a deleterious effect on GUS expression suggesting that these proteins were cytotoxic at the levels expressed. Analysis of replication of the InPAct vectors by Southern hybridisation revealed low levels of InPAct cassette-based episomal DNA released from the vector through the nicking/ligation activity of BBTV Rep. However, Rep-mediated episomal replicons, indicative of rolling circle replication of the released circularised cassettes, were not observed. The inability of the InPAct cassette to be replicated was further investigated. To examine whether the absence of Domain III of the CR-M was responsible, a suite of modified BBTV-based InPAct GUS vectors was constructed that contained the CR-M with the inclusion of Domain III, the CR-M with the inclusion of Domain III and additional upstream IR sequence, or no CR-M. Analysis of replication by Southern hybridisation revealed that neither the presence of Domain III, nor the entire CR-M, had an effect on replication levels. Since the InPAct cassette was significantly larger than the native BBTV genomic components (approximately 1 kb), the effect of InPAct cassette size on replication was also investigated. A suite of size variant BBTV-based vectors was constructed that increased the size of a replication competent cassette to 1.1 kbp through to 2.1 kbp.. Analysis of replication by Southern hybridisation revealed that an increase in vector size above approximately 1.5 - 1.7 kbp resulted in a decrease in replication. Following the demonstration of Rep-mediated release, circularisation and expression from the InPAct GUS vector, an InPAct vector was generated in which the uidA reporter gene was replaced with the ribonuclease-encoding suicide gene, barnase. Initially, a TEST vector was generated to assess the cytotoxicity of Barnase on banana cells. Although transient assays revealed a Barnase-induced cytotoxic effect in banana cells, the expression levels were sub-optimal. An InPAct BARNASE vector was generated and tested for BBTV Rep-activated Barnase expression using transient assays in banana embryogenic cells. High levels of background expression from the InPAct BARNASE vector made it difficult to accurately assess Rep-activated Barnase expression. Analysis of replication by Southern hybridisation revealed low levels of InPAct cassette-based episomal DNA released from the vector but no Rep-mediated episomal replicons indicative of rolling circle replication of the released circularised cassettes were again observed. Despite the inability of the InPAct vectors to replicate to enable high level gene expression, the InPAct BARNASE vector was assessed in planta for BBTV Rep-mediated activation of Barnase expression. Eleven lines of transgenic InPAct BARNASE banana plants were generated by Agrobacterium-mediated transformation and were challenged with viruliferous Pentalonia nigronervosa. At least one clonal plant in each line developed bunchy top symptoms and infection was confirmed by PCR. No localised lesions were observed on any plants, nor was there any localised GUS expression in the one InPAct GUS line challenged with viruliferous aphids. The results presented in this thesis are the first study towards the development of a BBTV-based InPAct system as a Rep-activatable suicide gene expression system to control BBTV. Although further optimisation of the vectors is necessary, the preliminary results suggest that this approach has the potential to be an effective control strategy for BBTV. The use of iterons within the InPAct vectors that are recognised by Reps from different ssDNA plant viruses may provide a broad-spectrum resistance strategy against multiple ssDNA plant viruses. Further, this technology holds great promise as a platform technology for the molecular farming of high-value proteins in vitro or in vivo through expression of the ssDNA virus Rep protein.

Knowledge-Based Urban Development : Planning and Applications in the Information Era

In the globalizing world, knowledge and information (and the social and technological settings for their production and communication) are now seen as keys to economic prosperity. The economy of a knowledge city creates value-added products using research, technology, and brainpower. The social benefit of knowledge-based urban development (KBUD); however, extends beyond aggregate economic growth.

A collaborative digestion and design game for community and technology exploration

In this paper, we present interim results from the Communities and Place project, which is exploring methods for understanding communities in a variety of contexts, and how to inform the design of technology to support them. We report on our experience with adapting an existing game-based approach for working with video as a resource in participatory design processes. Our adaptations allow the approach to be used with diverse data arising out of the different communities we are engaged with, and different design traditions we approach the problem from, leading to the formation of common design themes to inform our future work on this project.

Now everything looks like a game : Mobile phones and location-based games.

This paper explores how we may transform peoples’ perceived access to cultural participation by exploiting the possible relationships between place, play and mobile devices. It presents SCOOT; a location-based game in order to investigate how aspects of game-play can be employed to evoke at once playful and culturally meaningful experiences of place. In particular this paper is concerned with how the portable, communicative and social affordances of mobile phones are integral to making a “now everything looks like a game” experience.

Cipher cities : effective user interface design for building a digital social network around location-based gaming

In this paper we explore what is required of a User Interface (UI) design in order to encourage participation around playing and creating Location-Based Games (LBGs). To base our research in practice, we present Cipher Cities, a web based system. Through the design of this system, we investigate how UI design can provide tools for complex content creation to compliment and encourage the use of mobile phones for designing, distributing, and playing LBGs. Furthermore we discuss how UI design can promote and support socialisation around LBGs through the design of functional interface components and services such as groups, user profiles, and player status listings.

Finding order in chaos : a problem based collaborative assignment for 1300 students across 19 disciplines

The use of collaborative assignments for assessment is a risky undertaking for students and course designers. Yet the benefits, in terms of core learning outcomes, competencies, collaborative sense making and student involvement, suggest that the effort is worthwhile. Formal descriptions and rules do little to ameliorate the perception of risk and increased anxiety by students. (Ryan, 2007). BEB100 Introducing Professional Learning is a faculty-wide foundation unit with over 1300 students from 19 disciplines across the Faculty of the Built Environment and Engineering (“BEE”) at the Queensland University of Technology (“QUT”), Brisbane, Australia. Finding order in chaos outlines the approach and justification, assessment criteria, learning resources, teamwork tools, tutorial management, communication strategies, 2007-09 Student Learning Experience Survey results, annual improvements, findings and outcomes.

Technology strategy : findings from adoption and adaptation of Japanese manufacturing management (JMM) to ASEAN and Australasian automotive manufacturers

The purpose of this study is to demonstrate the appropriateness of “Japanese Manufacturing Management” (JMM) strategies in the Asian, ASEAN and Australasian automotive sectors. Secondly, the study assessed JMM as a prompt, effective and efficient global manufacturing management practice for automotive manufacturing companies to learn; benchmark for best practice; acquire product and process innovation, and enhance their capabilities and capacities. In this study, the philosophies, systems and tools that have been adopted in various automotive manufacturing assembly plants and their tier 1 suppliers in the three Regions were examined. A number of top to middle managers in these companies were located in Thailand, Indonesia, Malaysia, Singapore, Philippines, Viet Nam, and Australia and were interviewed by using a qualitative methodology. The results confirmed that the six pillars of JMM (culture change, quality at shop floor, consensus, incremental continual improvement, benchmarking, and backward-forward integration) are key enablers to success in adopting JMM in both automotive and other manufacturing sectors in the three Regions. The analysis and on-site interviews identified a number of recommendations that were validated by the automotive manufacturing company’s managers as the most functional JMM strategies.

Experience of problem-based learning (PBL) in virtual space : a phenomenographical study

This thesis reports the outcomes of an investigation into students’ experience of Problem-based learning (PBL) in virtual space. PBL is increasingly being used in many fields including engineering education. At the same time many engineering education providers are turning to online distance education. Unfortunately there is a dearth of research into what constitutes an effective learning experience for adult learners who undertake PBL instruction through online distance education. Research was therefore focussed on discovering the qualitatively different ways that students experience PBL in virtual space. Data was collected in an electronic environment from a course, which adopted the PBL strategy and was delivered entirely in virtual space. Students in this course were asked to respond to open-ended questions designed to elicit their learning experience in the course. Data was analysed using the phenomenographical approach. This interpretative research method concentrated on mapping the qualitative differences in students’ interpretations of their experience in the course. Five qualitatively different ways of experiencing were discovered: Conception 1: ‘A necessary evil for program progression’; Conception 2: ‘Developing skills to understand, evaluate, and solve technical Engineering and Surveying problems’; Conception 3: ‘Developing skills to work effectively in teams in virtual space’; Conception 4: ‘A unique approach to learning how to learn’; Conception 5: ‘Enhancing personal growth’. Each conception reveals variation in how students attend to learning by PBL in virtual space. Results indicate that the design of students’ online learning experience was responsible for making students aware of deeper ways of experiencing PBL in virtual space. Results also suggest that the quality and quantity of interaction with the team facilitator may have a significant impact on the student experience in virtual PBL courses. The outcomes imply pedagogical strategies can be devised for shifting students’ focus as they engage in the virtual PBL experience to effectively manage the student learning experience and thereby ensure that they gain maximum benefit. The results from this research hold important ramifications for graduates with respect to their ease of transition into professional work as well as their later professional competence in terms of problem solving, ability to transfer basic knowledge to real-life engineering scenarios, ability to adapt to changes and apply knowledge in unusual situations, ability to think critically and creatively, and a commitment to continuous life-long learning and self-improvement.

SNP technologies for drug discovery : a current review

Single nucleotide polymorphisms (SNPs) are unique genetic differences between individuals that contribute in significant ways to the determination of human variation including physical characteristics like height and appearance as well as less obvious traits such as personality, behaviour and disease susceptibility. SNPs can also significantly influence responses to pharmacotherapy and whether drugs will produce adverse reactions. The development of new drugs can be made far cheaper and more rapid by selecting participants in drug trials based on their genetically determined response to drugs. Technology that can rapidly and inexpensively genotype thousands of samples for thousands of SNPs at a time is therefore in high demand. With the completion of the human genome project, about 12 million true SNPs have been identified to date. However, most have not yet been associated with disease susceptibility or drug response. Testing for the appropriate drug response SNPs in a patient requiring treatment would enable individualised therapy with the right drug and dose administered correctly the first time. Many pharmaceutical companies are also interested in identifying SNPs associated with polygenic traits so novel therapeutic targets can be discovered. This review focuses on technologies that can be used for genotyping known SNPs as well as for the discovery of novel SNPs associated with drug response.

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.

Quality-based benefit design in health insurance : the impact of a product benefit design change on the utilisation of oral health services by members of a private health insurance fund in regional and rural New South Wales, Australia

Objective: To examine the impact on dental utilisation following the introduction of a participating provider scheme (Regional and Rural Oral Health Program {RROHP)). In this model dentists receive higher third party payments from a private health insurance fund for delivering an agreed range of preventive and diagnostic benefits at no out-ofpocket cost to insured patients. Data source/Study setting: Hospitals Contribution Fund of Australia (HCF) dental claims for all members resident in New South Wales over the six financial years from l99811999 to 200312004. Study design: This cohort study involves before and after analyses of dental claims experience over a six year period for approximately 81,000 individuals in the intervention group (HCF members resident in regional and rural New South Wales, Australia) and 267,000 in the control group (HCF members resident in the Sydney area). Only claims for individuals who were members of HCF at 31 December 1997 were included. The analysis groups claims into the three years prior to the establishment of the RROHP and the three years subsequent to implementation. Data collection/Extraction methods: The analysis is based on all claims submitted by users of services for visits between 1 July 1988 and 30 June 2004. In these data approximately 1,000,000 services were provided to the intervention group and approximately 4,900,000 in the control group. Principal findings: Using Statistical Process Control (SPC) charts, special cause variation was identified in total utilisation rate of private dental services in the intervention group post implementation. No such variation was present in the control group. On average in the three years after implementation of the program the utilisation rate of dental services by regional and rural residents of New South Wales who where members of HCF grew by 12.6%, over eight times the growth rate of 1.5% observed in the control group (HCF members who were Sydney residents). The differences were even more pronounced in the areas of service that were the focus of the program: diagnostic and preventive services. Conclusion: The implementation of a benefit design change, a participating provider scheme, that involved the removal of CO-payments on a defined range of preventive and diagnostic dental services combined with the establishment and promotion of a network of dentists, appears to have had a marked impact on HCF members' utilisation of dental services in regional and rural New South Wales, Australia.

Review of vibration-based damage detection and condition assessment of bridge structures using structural health monitoring

As a part of vital infrastructure and transportation networks, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs always make the infrastructure owners difficult to undertake. Structural health monitoring (SHM) is set to assess condition and foresee probable failures of designated bridge(s), so as to monitor the structural health of the bridges. The SHM systems proposed recently are incorporated with Vibration-Based Damage Detection (VBDD) techniques, Statistical Methods and Signal processing techniques and have been regarded as efficient and economical ways to solve the problem. The recent development in damage detection and condition assessment techniques based on VBDD and statistical methods are reviewed. The VBDD methods based on changes in natural frequencies, curvature/strain modes, modal strain energy (MSE) dynamic flexibility, artificial neural networks (ANN) before and after damage and other signal processing methods like Wavelet techniques and empirical mode decomposition (EMD) / Hilbert spectrum methods are discussed here.

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.