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A Blockchain Model for Superannuation Payments: Detecting Unpaid Super
No full textThe aim of this study is to develop a new process model and information system to detect superannuation fraud and assist Australian workers by identifying unpaid and unsettled superannuation through payroll activities. Employers set aside superannuation funds to provide their employees with a dignified retirement. According to some studies, employers may fail to make required contributions to an employee's superannuation fund, make correct payments, or debit the incorrect fund in violation of legal or contractual obligations. To address these issues, the Australian federal government has enacted laws and regulations to ensure that employers meet their contribution obligations. Despite these safeguards and highly secured information systems, there has been a significant increase in fraudulent activity in the financial sector, and there have been several instances of employers not making contributions, misusing retirement funds, or incorrectly reporting in systems. The current process restricts employee access to recent data until the contributions reach their superannuation fund, leaving the door open for fraud. In recent years, blockchain technology has become increasingly popular due to its capacity to enhance security and transparency and prevent fraud in numerous industries, including finance. Prior research has provided insights, though limited, into how to prevent pension fraud. In addition, the literature on the potential use of blockchain technology to address this issue is scant. Consequently, this study introduces a novel process model and creates a blockchain-based application to prevent fraudulent practices. To address the challenges, this study maps out the existing superannuation payment process, identifies the critical areas and presents a blockchain-based model for the superannuation contribution process. Although blockchain technology is prevalent in numerous industries, it has not yet been implemented in superannuation payments. Consequently, the blockchain-based model is devised after examining the discrepancies in the current superannuation payment process and the characteristics of blockchain technology. This study found the proposed blockchain technology model to be an ideal solution for detecting unpaid superannuation due to its ability to eliminate transparency issues of transactions. This study offers valuable insights into the design of innovative process models that employ blockchain technology to address superannuation issues. As well, the thesis provides an example of a simulated smart contract to investigate additional implications and developments in this field.</p
Achieving social sustainability through long-term planning of a coastal tourism destination threatened by climate change - A study of Livingstone Shire, Queensland.
No full textIn coming decades coastal tourism destinations will become increasingly vulnerable to the impacts of climate change including extreme weather events, ecosystem damage, increased sea levels and flooding. These changes are likely to have a detrimental effect on destination economies and welfare of the local communities. While these changes are likely to occur over several decades or more, it is essential that the local authorities administrating these destinations begin planning to deal with the impacts of climate change as soon as possible. Planning should consider and re-evaluate the impacts of climate change regularly to avoid future vulnerabilities and destructions to achieve long-term climate resilience. This requires considerable understanding and knowledge of the threats posed by climate change, impacts of climate change at the local level, climate adaptation, resilience options at the local scale and social sustainability of the destination community. One important issue that local authorities need to consider as part of this process is the impact of long-term climate change on the social sustainability of a destination’s population. Based on these needs, the aim of this research was to explore opportunities for a coastal tourism destination community threatened by climate change to improve and strengthen social sustainability by employing collaborative planning strategies as an element of its long-term destination planning. The research was undertaken in the Livingstone Shire, Queensland, a coastal tourism destination that has identified tourism as a key element of the local economy. A review of the literature identified several gaps including a paucity of studies that have explored pathways for achieving social sustainability within communities in coastal tourism destinations. Other gaps included strategies to maintain social sustainability in a coastal tourism destination threatened by climate change and opportunities for using collaborative planning strategies to achieve social sustainability in destinations of this type. To address these gaps, four research objectives were developed to: Determine the views of the government and local community on current and projected tourism development proposals for the Livingstone Shire region.Identify the key concerns of the government and the local community on climate change and its potential impacts for the Livingstone Shire region.Identify key concerns about achieving long-term social sustainability in the Livingstone Shire region.Develop a suitable model that can be adopted to ensure that the views of the government and community are more effectively incorporated into long-term, socially sustainable coastal tourism destination planning and development. This study adopted a constructivist paradigm with inductive reasoning to achieve comprehensive knowledge of the research problem. Qualitative data was gathered by conducting semi-structured interviews with representatives of the local government and community. Thematic analysis using NVIVO enabled the identification and coding of key themes from transcribed interviews. The research process was subjective, and qualitative findings were obtained from an insider’s perspective in a real-world setting. The key themes were identified by research objectives. The key themes for research objective 1 (RO1) were resorts, aspirations for the future, infrastructure, lifestyle and concerns around over-tourism, opportunities for new attractions and opportunities for collaboration. The key themes for research objective 2 (RO2) were the climate impacts and threats, concerns over extreme weather events, Great Barrier Reef (GBR) and response to climate change (climate adaptation, mitigation and resilience). The key theme for research objective 3 (RO3) focused on concerns about achieving long-term social sustainability. The findings related to the key themes identified in RO1, RO2 and RO3 were organised into a framework that identifies the hierarchical stages and levels involved in achieving social sustainability in response to the impacts of climate change. This framework was then used to develop a model that can be used as a tool for achieving social sustainability, outlining the inputs required and actors involved, and ensuring that the views of the government and community are more effectively incorporated into long-term, sustainable coastal tourism destination planning and development. The model highlights that social sustainability can be achieved through a three-stage process, but its ongoing maintenance requires a fourth stage of monitoring and evaluation in the form of a loop where all inputs can be subject to ongoing evaluation over time. In addition to those features, maintenance social sustainability also requires a destination's local government to develop a management structure or a system that will continue to identify and monitor any gaps in the process, and fill those gaps to ensure a high intergenerational level of social sustainability. The key contributions of this research include a deeper understanding of the processes that destinations need to progress through to achieve social sustainability and the need for ongoing maintenance of social responsibility as a strategy for responding to climate change. A major limitation of the research was that it only considered one coastal destination. Larger destinations may face other issues not identified in this research. Moreover, the study only focused on one level of government. Other levels of government, including the state government, may also impact on the issues discussed. Finally, the views obtained from the interview participants may not be representative of the entire community of Livingstone Shire.</p
A blockchain technology model for detecting and preventing superannuation fraud
No full textThe Australian government introduced a superannuation scheme to provide workers with savings for retirement. Superannuation is one of the most valuable assets of the majority of Australians. The scheme requires employers to set aside superannuation funds to provide their employees with a dignified retirement. However, some employers failed to make the required contributions to their employees’ superannuation funds. Moreover, some did not make correct payments or debit the incorrect funds in violation of legal obligations. To prevent fraud and to ensure both employers and their workers have access to employer contributions information, a robust superannuation system is essential. This paper aims to assess the suitability of blockchain technology for addressing the challenges of detecting and preventing superannuation fraud. Prior studies suggest that blockchain technology has not yet been used in the superannuation sector. The proposed research will involve reviewing the literature on disruptive technologies to determine the most compatible ones for these tasks. The results of the research will contribute to the disruptive technology models literature and support the superannuation industry by improving accuracy in superannuation contribution and budgeting
Confronting and alleviating AI resistance in the workplace: An integrative review and a process framework
No full textThis study involves an integrative literature review and a process framework explaining the mechanisms to confront and alleviate employee Artificial intelligence (AI) resistance in organizations. First, we conceptualize AI resistance as a three-dimensional concept embodied in employees' fears, inefficacies, and antipathies toward AI. We advance that experiencing mistrust, existential questioning, and technological reflection are key individual mechanisms to confronting AI resistance connected to organizational mechanisms to alleviate AI resistance through the continuous interaction and unfolding of anxiety and introspection. We also explain the alleviation of AI resistance as an organizational process consisting of AI accessibility, human-AI augmentation, and AI-technology legitimation, each of which maps into one of the dimensions in the employee-level confrontation mechanisms. Overall, our conceptual framework provides an overarching and granular understanding of AI resistance, how employees confront it, and how it can be alleviated in the workplace.</p
Decoding neural signals: Invasive BMI review
No full textHuman civilization has witnessed transformative technological milestones, from ancient fire-lighting to the internet era. This chapter delves into the invasive brain-machine interface (BMI), a pioneering technology poised to be a defining chapter in our progress. Beyond aiding medical conditions, invasive BMI promises far-reaching impacts across diverse technologies and aspects of life. The exploration begins by unraveling the biological and engineering principles essential for BMI implementation. The chapter comprehensively analyzes potential applications, methodologies for detecting and decoding brain signals, and options for stimulating signals within the human brain. It concludes with a discussion on the multifaceted challenges and opportunities for the continued development of invasive BMI. This chapter not only provides a profound understanding of the foundational elements of invasive BMI but also serves as a guide through its applications, intricacies, and potential societal implications. Navigating neurobiology, engineering innovations, and the evolving landscape of human-AI symbiosis, the chapter sheds light on the promises and hurdles that define the future of invasive BMI
‘Before and after’. The journey of patients with low back pain consulting in elective spine surgery clinics. A qualitative study protocol
No full textIntroduction: Low back pain (LBP) is a highly prevalent and disabling condition. People with LBP may be referred to elective surgical clinics for further evaluation and consideration of surgery. Despite long waits for an initial appointment, many of these patients are not surgical candidates and may be discharged, receiving minimal-to-no care, advice or alternative treatment options, leaving a critical gap in care. Methods: Approximately 25 participants with dominant, chronic non-specific axial LBP who are (1) referred to and (2) discharged without spinal surgery following consultation in two elective spinal surgery clinics in Western Australia will participate in a one-on-one pre-consultation semi-structured interview and a similar post-consultation qualitative interview. Purposive sampling will be used to recruit participants. Interviews will be audio-recorded and transcribed, underpinned by a qualitative descriptive approach to explore participants' care journey, including pre-consultation expectations and overall experiences post-consultation. We will use inductive content analysis to analyse our data, allowing for the identification of themes that are generated from the participants' responses. Discussion/Conclusion: This protocol outlines the methodological process for a qualitative study exploring the experiences and expectations of LBP patients before and after consulting in elective spinal surgery clinics in Western Australia. The findings may give rise to consumer-focused solutions to improve the care journey and highlight gaps in patient expectations and understanding of non-surgical management, informing the development of tailored educational resources, communication strategies and new care pathways. Patient or Public Contribution: This study will incorporate patient and/or public involvement by engaging representatives from Musculoskeletal Australia (https://muscha.org/) to contribute to the study design and interpretation of findings. Specifically, a consumer with lived experience of low back pain will be invited to review and provide feedback on the semi-structured interview questions, to ensure they are appropriate, accessible and reflective of patient experiences. Clinical Trial Registration: This study is not a clinical trial and is therefore not registered.</p
Improving Sleep Through Behaviour Change: A Mixed-Methods Investigation to Understand and Reduce Bedtime Procrastination in New Career Starters
No full textInadequate sleep is a prevalent public health issue with negative consequences for physical and mental well-being, as well as economic productivity. Bedtime procrastination, the volitional delay of going to bed without any external circumstances causing the delay, is a modifiable health behaviour that can contribute to inadequate sleep. Targeting bedtime procrastination in populations vulnerable to inadequate sleep, such as new career starters, is a novel approach that holds promise in improving sleep outcomes. The primary aim of this thesis was to develop a theory-based behaviour change intervention to target bedtime procrastination in new career starters. The secondary aim was to undertake formative work to understand the correlates of bedtime procrastination, as well as to identify specific bedtime procrastination behaviours in new career starters. This thesis utilized a mixed-methods design across four studies. Study One systematically reviewed and meta-analysed the literature to identify correlates of bedtime procrastination and the relationship of bedtime procrastination with sleep outcomes. Study Two qualitatively explored the experiences of new career starters to understand the motivations to procrastinate bedtime and the pre-sleep behaviours used to procrastinate. Study Three examined the influence of hedonic and reflective motivation on pre-sleep electronic device use in new career starters using ecological momentary assessment. Finally, Study Four examined the feasibility and efficacy of a theory-based behaviour change intervention to reduce pre-sleep electronic device use and bedtime procrastination in new career starters. Collectively, there were five key findings from the studies presented in this thesis: (1) bedtime procrastination is associated with shorter sleep duration, lower sleep quality, increased daytime fatigue, and is prevalent in new career starters; (2) bedtime procrastination is characterised by the interaction of both reflective and automatic cognitive processes, and bedtime procrastination behaviours can be explained by dual-process theories; (3) hedonic motivation, the impulsive desire for pleasure and to avoid displeasure, plays a key role in pre-sleep electronic device use, the most prevalent bedtime procrastination behaviour in new career starters; (4) behaviour change interventions show promise in reducing bedtime procrastination, evidenced by a mean pre-post intervention change in pre-sleep electronic device use of 28.7 minutes per day (45% decrease) and 23.1 minutes per day (53% decrease) in experimental groups in the Reducing Evening Screen Time Online pilot intervention (REST-O) program; and (5) a harm minimisation approach to pre-sleep electronic device use can be effective, demonstrated through the use of personalised behavioural substitution in the REST-O pilot intervention. The findings of this thesis have established bedtime procrastination as a distinct research area, and have several further contributions to the field. This thesis proposes that dual-process theories can explain bedtime procrastination behaviours, moving beyond a focus on self-regulation to acknowledge the influence of automatic processes. In designing interventions in sleep health, this thesis also highlights the importance of considering specific pre-sleep behaviours and their behavioural outcomes. Additionally, the findings of this thesis responded to calls to apply theory-based dual-process approaches to sleep health, offering initial evidence of the effectiveness of this approach in improving sleep and behavioural outcomes. Future work should prioritise how bedtime procrastination is experienced in other populations with disturbed and disordered sleep, such as new parents or caregivers, and in those with insomnia or obstructive sleep apnoea. Further, researchers should investigate the relationship between bedtime procrastination and sleep regularity, two phenomena with shared outcomes. Future public health messaging and interventions could potentially leverage popular interest in bedtime procrastination to promote awareness of the importance of sleep regularity to health. Additionally, there is promise in exploring the role technology companies can play in integrating evidence-based interventions into products, such as smartphone and smartwatch operating systems, to boost intervention accessibility and uptake. Overall, this thesis provides a foundation for developing and implementing theory-based dual-process interventions to target bedtime procrastination and promote sleep health in new career starters. Future efforts, in new career starters and beyond, can build on this approach in encouraging healthier pre-sleep behaviours to improve sleep outcomes and public health.</p
Foreign Aid Governance and Management in Sierra Leone Towards A Comprehensive Approach
No full textAs global donor fatigue increases, developing countries that rely on international donors must find more sustainable fiscal and monetary security methods. This thesis examines how foreign aid is managed in Sierra Leone and aims to explore alternative ways for foreign aid management and governance. How is foreign aid currently managed in Sierra Leone, and what are the main challenges associated with its governance? What alternative approaches can be adopted for more effective and sustainable management of foreign aid in Sierra Leone? What framework can ensure better governance and management of foreign aid in Sierra Leone, leading to enhanced fiscal self-reliance? These questions come on the back of Sierra Leone’s unenviable political and economic profile in the context of the exigencies of the current political and economic challenges. Sierra Leone’s post-independent history is riddled with events of political instability, including a decade-long civil war between 1991 and 2002 and the Ebola pandemic of 2014. Unsurprisingly, Sierra Leone has required foreign aid to augment its developmental agenda, which makes the country vulnerable to global economic pressures. The study applied six governance indicators and strands identified by the United Nations Development Programme (UNDP) and Kaufmann et al. (1999) as its conceptual framework: the Rule of Law, Effectiveness, Accountability, Corruption Monitoring, Strategic Vision, and Donor Policies. These standards and indicators provide a multifaceted approach to assessing foreign aid management in Sierra Leone, ensuring legal and administrative efficiency, ethical governance, and strategic alignment with donor policies for sustainable development. Research on governance and law as foundational for development are instrumental in addressing the challenges of foreign aid-dependent development programs in Sierra Leone. The indicators promote the efficient and transparent utilisation of foreign aid by ensuring a robust legal framework and effective governmental structures. The emphasis on accountability and corruption monitoring, for instance, safeguards against misappropriation of funds, ensuring aid reaches its intended targets. Strategic vision aligns aid with national priorities, ensuring sustainability while understanding donor policies to help navigate external influences. Collectively, these indicators provide a comprehensive approach to strengthening governance and institutional capacities in Sierra Leone, enhancing the effectiveness of foreign aid, and reducing dependency by fostering sustainable development practices and self-reliance. The study applied these indicators to the perspectives of 11 officials, consisting of five females and six males, who were directly involved in the management of three aid-funded projects in i Sierra Leone. It employed a thematic analysis involving identifying, analysing, and reporting patterns (themes). The study followed four steps in procession and preparing the data, including normalisation, reduction, analysis and coding, and transformation. Data reduction techniques were employed to filter and categorise the data into more manageable and analysable units. The filtering process identified and focused on the most relevant aspects of the data that directly addressed the research questions, while categorisation classified the data into distinct themes along the six indicators to find patterns in areas of concern and suggested recommendations for alternative and comprehensive aid governance.The study made several arguments. First, while the development utility of aid is mixed in the African context, the problem is not that aid is inherently a problem. Instead, the problem is how aid funds are managed. This argument is a middle ground between those who advocate for more aid under current regimes of overseas development assistance (ODA) programs, and those who reject aid outrightly. Secondly, in the context of Sierra Leone, the study finds that while the country has made significant strides in addressing the conditions that detract from the benefits of receiving aid—i.e. the above indicators—the governance of foreign aid is still lacking in two crucial areas: firstly, it does not acknowledge the adverse consequences of the macro level strategic self-interests of global donor actors; and, secondly, there is little or no involvement of micro-level factors, such as the interests and agency of citizens and local communities. The study, therefore, concludes that more effective, self-reliant, comprehensive, and sustainable foreign aid management can emerge from inculcating these two factors into aid governance. Thus, the thesis proposes a framework comprising eight indicators, including the six plus the two identified from the experiences of the 11 respondents. The study not only brings fresh perspectives on aid governance in Sierra Leone but also offers a lens and a framework through which aid could be effectively managed during severe global economic pressure and austerity.</p
A randomised pilot trial for bedtime procrastination: the Reducing Evening Screen Time online intervention (REST-O)
No full textFollowing the development of a behaviour change intervention for bedtime procrastination, this is a pilot study of the intervention program.</p
Next generation crop protection: A systematic review of trends in modelling approaches for disease prediction
No full textDigital agriculture tools and advances in modelling approaches have the potential to deliver precise decision support systems for more effective, efficient and sustainable crop disease management. Historically, disease prediction in agriculture has relied on knowledge of the relationships between a few key environmental parameters and crop disease development. The emergence of new sensor technologies is now expanding the range of input data readily accessible for use in modelling. In addition, Artificial Intelligence (such as machine learning and deep learning algorithms) offers the capacity to process the large datasets available from a wider range of input variables relating to the three components of disease development: host, pathogen and environment. This review examined the rate and extent to which machine learning has replaced traditional modelling approaches for disease predictive model development. A systematic protocol was developed to investigate trends in modelling approaches for disease prediction in four major crop types: cereals, grape, potato and citrus. A total of 104 publications, reporting on the development of 146 disease predictive models were evaluated for modelling approach, data inputs and model performance. The results from this review indicate that the application of machine learning for predictive model development has greatly increased over the past two decades. Increased application of machine learning models (including Support Vector Machine and Random Forest) was associated with the development of more high-performance models and incorporation of higher numbers of predictor variables. The potential of deep learning models to deliver more precise and adaptable models for next generation disease management will be determined by applying these methods to large datasets. Further research is needed to investigate multi-model, machine learning approaches for disease prediction and to ensure model design captures important input variables relating to environment, host and pathogen.</p