Entrepreneurship education in non-business schools : best practice for Australian contexts of knowledge and innovation communities (Final Report)

In the current era of global economic instability, business and industry have already identified a widening gap between graduate skills and employability. An important element of this is the lack of entrepreneurial skills in graduates. This Teaching Fellowship investigated two sides of a story about entrepreneurial skills and their teaching. Senior players in the innovation commercialisation industry, a high profile entrepreneurial sector, were surveyed to gauge their needs and experiences of graduates they employ. International contexts of entrepreneurship education were investigated to explore how their teaching programs impart the skills of entrepreneurship. Such knowledge is an essential for the design of education programs that can deliver the entrepreneurial skills deemed important by industry for future sustainability. Two programs of entrepreneurship education are being implemented at QUT that draw on the best practice exemplars investigated during this Fellowship. The QUT Innovation Space (QIS) focuses on capturing the innovation and creativity of students, staff and others. The QIS is a physical and virtual meeting and networking space; a connected community enhancing the engagement of participants. The Q_Hatchery is still embryonic; but it is intended to be an innovation community that brings together nascent entrepreneurial businesses to collaborate, train and support each other. There is a niche between concept product and business incubator where an experiential learning environment for otherwise isolated ‘garage-at-home’ businesses could improve success rates. The QIS and the Q_Hatchery serve as living research laboratories to trial the concepts emerging from the skills survey. The survey of skills requirements of the innovation commercialisation industry has produced a large and high quality data set still being explored. Work experience as an employability factor has already emerged as an industry requirement that provides employee maturity. Exploratory factor analysis of the skills topics surveyed has led to a process-based conceptual model for teaching and learning higher-order entrepreneurial skills. Two foundational skills domains (Knowledge, Awareness) are proposed as prerequisites which allow individuals with a suite of early stage entrepreneurial and behavioural skills (Pre-leadership) to further leverage their careers into a leadership role in industry with development of skills around higher order elements of entrepreneurship, management in new business ventures and progressing winning technologies to market. The next stage of the analysis is to test the proposed model through structured equation modelling. Another factor that emerged quickly from the survey analysis broadens the generic concept of team skills currently voiced in Australian policy documents discussing the employability agenda. While there was recognition of the role of sharing, creating and using knowledge in a team-based interdisciplinary context, the adoption and adaptation of behaviours and attitudes of other team members of different disciplinary backgrounds (interprofessionalism) featured as an issue. Most undergraduates are taught and undertake teamwork in silos and, thus, seldom experience a true real-world interdisciplinary environment. Enhancing the entrepreneurial capacity of Australian industry is essential for the economic health of the country and can only be achieved by addressing the lack of entrepreneurial skills in graduates from the higher education system. This Fellowship has attempted to address this deficiency by identifying the skills requirements and providing frameworks for their teaching.

Time pressure and coworker support mediate the curvilinear relationship between age and occupational well-being

As the proportion of older employees in the workforce is growing, researchers have become increasingly interested in the association between age and occupational well-being. The curvilinear nature of relationships between age and job satisfaction and between age and emotional exhaustion is well-established in the literature, with employees in their late 20s to early 40s generally reporting lower levels of occupational well-being than younger and older employees. However, the mechanisms underlying these curvilinear relationships are so far not well understood due to a lack of studies testing mediation effects. Based on an integration of role theory and research from the adult development and career literatures, this study examined time pressure, work–home conflict, and coworker support as mediators of the relationships between age and job satisfaction and between age and emotional exhaustion. Data came from 771 employees between 17 and 74 years of age in the construction industry. Results showed that employees in their late 20s to early 40s had lower job satisfaction and higher emotional exhaustion than younger and older employees. Time pressure and coworker support fully mediated both the U-shaped relationship between age and job satisfaction and the inversely U-shaped relationship between age and emotional exhaustion. These findings suggest that organizational interventions may help increase the relatively low levels of occupational well-being in certain age groups.

Integration of XML Schemas for the Exchange of FDOT Construction Project Data

An investigation of the construction data management needs of the Florida Department of Transportation (FDOT) with regard to XML standards including development of data dictionary and data mapping. The review of existing XML schemas indicated the need for development of specific XML schemas. XML schemas were developed for all FDOT construction data management processes. Additionally, data entry, approval and data retrieval applications were developed for payroll compliance reporting and pile quantity payment development.

Carcinoma ex pleomorphic adenoma : a comprehensive review of clinical, pathological and molecular data

Carcinoma ex pleomorphic adenoma (Ca ex PA) is a carcinoma arising from a primary or recurrent benign pleomorphic adenoma. It often poses a diagnostic challenge to clinicians and pathologists. This study intends to review the literature and highlight the current clinical and molecular perspectives about this entity. The most common clinical presentation of CA ex PA is of a firm mass in the parotid gland. The proportion of adenoma and carcinoma components determines the macroscopic features of this neoplasm. The entity is difficult to diagnose pre-operatively. Pathologic assessment is the gold standard for making the diagnosis. Treatment for Ca ex PA often involves an ablative surgical procedure which may be followed by radiotherapy. Overall, patients with Ca ex PA have a poor prognosis. Accurate diagnosis and aggressive surgical management of patients presenting with Ca ex PA can increase their survival rates. Molecular studies have revealed that the development of Ca ex PA follows a multi-step model of carcinogenesis, with the progressive loss of heterozygosity at chromosomal arms 8q, then 12q and finally 17p. There are specific candidate genes in these regions that are associated with particular stages in the progression of Ca ex PA. In addition, many genes which regulate tumour suppression, cell cycle control, growth factors and cell-cell adhesion play a role in the development and progression of Ca ex PA. It is hopeful that these molecular data can give clues for the diagnosis and management of the disease.

Robust multiple-sensing-modality data fusion using Gaussian Process Implicit Surfaces

The ability to build high-fidelity 3D representations of the environment from sensor data is critical for autonomous robots. Multi-sensor data fusion allows for more complete and accurate representations. Furthermore, using distinct sensing modalities (i.e. sensors using a different physical process and/or operating at different electromagnetic frequencies) usually leads to more reliable perception, especially in challenging environments, as modalities may complement each other. However, they may react differently to certain materials or environmental conditions, leading to catastrophic fusion. In this paper, we propose a new method to reliably fuse data from multiple sensing modalities, including in situations where they detect different targets. We first compute distinct continuous surface representations for each sensing modality, with uncertainty, using Gaussian Process Implicit Surfaces (GPIS). Second, we perform a local consistency test between these representations, to separate consistent data (i.e. data corresponding to the detection of the same target by the sensors) from inconsistent data. The consistent data can then be fused together, using another GPIS process, and the rest of the data can be combined as appropriate. The approach is first validated using synthetic data. We then demonstrate its benefit using a mobile robot, equipped with a laser scanner and a radar, which operates in an outdoor environment in the presence of large clouds of airborne dust and smoke.

Corporate sustainability reporting for water : water footprint, global reporting initiative and the water accounting framework

Three initiatives with respect to water reporting in the mining sector are compared in this paper to understand the quantities that are asked for by each initiative and the guidelines of those initiatives through means of a case study. The Global Reporting Initiative (GRI) was chosen because it has achieved widespread acceptance amongst mining companies and its water-related indicators are widely reported in corporate sustainability reporting. In contrast, the Water Footprint Network, which has been an important initiative in food and agricultural industries, has had low acceptance in the mining industry. The third initiative is the Water Accounting Framework, a collaboration between The Minerals Council of Australia and the Sustainable Minerals Institute of the University of Queensland. A water account had previously been created according to the Water Accounting Framework for the case study site, an open pit coal mine in the Bowen Basin. The resulting account provided consistent data for the Global Reporting Initiative (GRI) and the Water Footprint attributable to mining but in particular, a deficiency in the GRI indicator of EN10 reuse and recycling efficiency was illustrated quantitatively. This has far-reaching significance due to the widespread use of GRI indicators in mining corporate reports.

Plasmodium falciparum parasites lacking histidine-rich protein 2 and 3 : a review and recommendations for accurate reporting

Malaria rapid diagnostic tests (RDTs) play a critical role in malaria case management, surveillance and case investigations. Test performance is largely determined by design and quality characteristics, such as detection sensitivity, specificity, and thermal stability. However, parasite characteristics such as variable or absent expression of antigens targeted by RDTs can also affect RDT performance. Plasmodium falciparum parasites lacking the PfHRP2 protein, the most common target antigen for detection of P. falciparum, have been reported in some regions. Therefore, accurately mapping the presence and prevalence of P. falciparum parasites lacking pfhrp2 would be an important step so that RDTs targeting alternative antigens, or microscopy, can be preferentially selected for use in such regions. Herein the available evidence and molecular basis for identifying malaria parasites lacking PfHRP2 is reviewed, and a set of recommended procedures to apply for future investigations for parasites lacking PfHRP2, is proposed.

Outbreak detection algorithms for seasonal disease data : a case study using Ross River virus disease

Background Detection of outbreaks is an important part of disease surveillance. Although many algorithms have been designed for detecting outbreaks, few have been specifically assessed against diseases that have distinct seasonal incidence patterns, such as those caused by vector-borne pathogens. Methods We applied five previously reported outbreak detection algorithms to Ross River virus (RRV) disease data (1991-2007) for the four local government areas (LGAs) of Brisbane, Emerald, Redland and Townsville in Queensland, Australia. The methods used were the Early Aberration Reporting System (EARS) C1, C2 and C3 methods, negative binomial cusum (NBC), historical limits method (HLM), Poisson outbreak detection (POD) method and the purely temporal SaTScan analysis. Seasonally-adjusted variants of the NBC and SaTScan methods were developed. Some of the algorithms were applied using a range of parameter values, resulting in 17 variants of the five algorithms. Results The 9,188 RRV disease notifications that occurred in the four selected regions over the study period showed marked seasonality, which adversely affected the performance of some of the outbreak detection algorithms. Most of the methods examined were able to detect the same major events. The exception was the seasonally-adjusted NBC methods that detected an excess of short signals. The NBC, POD and temporal SaTScan algorithms were the only methods that consistently had high true positive rates and low false positive and false negative rates across the four study areas. The timeliness of outbreak signals generated by each method was also compared but there was no consistency across outbreaks and LGAs. Conclusions This study has highlighted several issues associated with applying outbreak detection algorithms to seasonal disease data. In lieu of a true gold standard, a quantitative comparison is difficult and caution should be taken when interpreting the true positives, false positives, sensitivity and specificity.

Mining business process deviance : a quest for accuracy

This paper evaluates the suitability of sequence classification techniques for analyzing deviant business process executions based on event logs. Deviant process executions are those that deviate in a negative or positive way with respect to normative or desirable outcomes, such as non-compliant executions or executions that undershoot or exceed performance targets. We evaluate a range of feature types and classification methods in terms of their ability to accurately discriminate between normal and deviant executions both when deviances are infrequent (unbalanced) and when deviances are as frequent as normal executions (balanced). We also analyze the ability of the discovered rules to explain potential causes and contributing factors of observed deviances. The evaluation results show that feature types extracted using pattern mining techniques only slightly outperform those based on individual activity frequency. The results also suggest that more complex feature types ought to be explored to achieve higher levels of accuracy.

Sewer performance reporting : factors that influence blockages

Managing sewer blockages represents a significant operational challenge for water utilities. In Australia, company-level blockage rates are used to compare the effectiveness of the management strategies of different utilities. Anecdotal evidence suggests this may not be a fair basis for comparison because blockages are influenced by a range of factors beyond management control and that vary from company to company. This issue was investigated as part of a broader research effort on sewer blockage management undertaken in conjunction with the Water Services Association of Australia (WSAA) and its members. A Web-based survey was used to collate expert opinion on factors that influence blockage rate. The identified factors were then investigated in an exploratory analysis of blockage-related data provided by two participating utilities, supported by literature reviews. The results indicate that blockage rate is influenced by a range of factors, including asset attributes, climatic conditions, water consumption, and soil type. Since these factors vary from utility to utility, this research supports the assertion that company-level blockage rate is not in itself an appropriate metric for comparing management effectiveness.

Understanding financial information used to assess small firm performance : an Australian qualitative study

Purpose The purpose of this paper is to investigate the reality of financial and management accounting in a small group of small firms. Specifically, from the owner's perspective, an exploration is undertaken to see what financial information is collected, how it is used (or not) to make business decisions and evaluate the firm's performance, and the role played by the accountant in that process. Design/methodology/approach A phenomenological paradigm underpins this exploratory study. Semi‐structured interviews were undertaken with the owners of ten small firms, where the focus was on understanding what happens in an organisational setting, as opposed to theory and textbook practice. Findings The qualitative data supported prior research in other countries. The in‐depth analysis revealed a very basic understanding of accounting information and problems with the financial literacy amongst these small firm owners. Accounting reports were not widely produced or used, so an informal assessment, such as how much cash was in the bank, was the primary means of assessing business performance. Accountants were used for taxation services, although some owners sought more general business advice. Originality/value An understanding is developed of why there might be a gap between textbook rhetoric and reality of accounting practice in small firms. The conclusion is that accounting textbooks need to include more information about the reality of financial management in small firms.

Informal e-learning : the case of small business owners

Purpose - The purpose of this paper is to investigate the use of an informal online discussion forum (ODF) to encourage voluntary participation and promote double-loop learning by small business owners (SBOs). Design/methodology/approach - A qualitative methodology was used where data gathered from three sources, the ODF posts, in-depth interviews with participants and a focus group with non-participants. These were analysed to evaluate learning of SBOs in an ODF. Findings - This research provides evidence that an ODF for SBOs supports double-loop learning; however, participation could not be assumed simply by the online availability of the discussion resource. Research limitations/implications - Few SBOs participated in the ODF which is consistent with research finding SBOs are a difficult group to engage in learning. Four forms of data were analysed to strengthen results. Practical implications - Caution should be exercised when considering investment in e-learning for SBOs. Originality/value - Evidence showing e-learning through an informal voluntary ODF can promote deep learning for SBOs.

Dataset validation within big data security architecture

In recent years, increasing focus has been made on making good business decisions utilizing the product of data analysis. With the advent of the Big Data phenomenon, this is even more apparent than ever before. But the question is how can organizations trust decisions made on the basis of results obtained from analysis of untrusted data? Assurances and trust that data and datasets that inform these decisions have not been tainted by outside agency. This study will propose enabling the authentication of datasets specifically by the extension of the RESTful architectural scheme to include authentication parameters while operating within a larger holistic security framework architecture or model compliant to legislation.

Improving national hospice/palliative care service symptom outcomes systematically through point-of-care data collection, structured feedback and benchmarking

PURPOSE Every health care sector including hospice/palliative care needs to systematically improve services using patient-defined outcomes. Data from the national Australian Palliative Care Outcomes Collaboration aims to define whether hospice/palliative care patients' outcomes and the consistency of these outcomes have improved in the last 3 years. METHODS Data were analysed by clinical phase (stable, unstable, deteriorating, terminal). Patient-level data included the Symptom Assessment Scale and the Palliative Care Problem Severity Score. Nationally collected point-of-care data were anchored for the period July-December 2008 and subsequently compared to this baseline in six 6-month reporting cycles for all services that submitted data in every time period (n = 30) using individual longitudinal multi-level random coefficient models. RESULTS Data were analysed for 19,747 patients (46 % female; 85 % cancer; 27,928 episodes of care; 65,463 phases). There were significant improvements across all domains (symptom control, family care, psychological and spiritual care) except pain. Simultaneously, the interquartile ranges decreased, jointly indicating that better and more consistent patient outcomes were being achieved. CONCLUSION These are the first national hospice/palliative care symptom control performance data to demonstrate improvements in clinical outcomes at a service level as a result of routine data collection and systematic feedback.

Exploring location-dependency in process modeling

Purpose – Context-awareness has emerged as an important principle in the design of flexible business processes. The goal of the research is to develop an approach to extend context-aware business process modeling toward location-awareness. The purpose of this paper is to identify and conceptualize location-dependencies in process modeling. Design/methodology/approach – This paper uses a pattern-based approach to identify location-dependency in process models. The authors design specifications for these patterns. The authors present illustrative examples and evaluate the identified patterns through a literature review of published process cases. Findings – This paper introduces location-awareness as a new perspective to extend context-awareness in BPM research, by introducing relevant location concepts such as location-awareness and location-dependencies. The authors identify five basic location-dependent control-flow patterns that can be captured in process models. And the authors identify location-dependencies in several existing case studies of business processes. Research limitations/implications – The authors focus exclusively on the control-flow perspective of process models. Further work needs to extend the research to address location-dependencies in process data or resources. Further empirical work is needed to explore determinants and consequences of the modeling of location-dependencies. Originality/value – As existing literature mostly focusses on the broad context of business process, location in process modeling still is treated as “second class citizen” in theory and in practice. This paper discusses the vital role of location-dependencies within business processes. The proposed five basic location-dependent control-flow patterns are novel and useful to explain location-dependency in business process models. They provide a conceptual basis for further exploration of location-awareness in the management of business processes.