Business

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Now showing 1 - 10 of 76
  • (2021) Ho, Tin Long
    Thesis
    Housing wealth is typically the largest component of retirees’ portfolios. Although economic theory predicts that retirees would benefit from using housing wealth as a source of retirement funding, the take-up of enabling products and approaches is low. This thesis addresses three key areas in the utilization of housing wealth in retirement: (i) identification of the preferred home equity release approach for different types of households; (ii) exploration of means to address behavioral impediments to the utilization of housing wealth through equity release products; (iii) investigation of potential demand for long-term care insurance (LTCI) financed through home equity release. Chapter 3 investigates the preferred home equity release approach for retirement, given available options (i.e., downsizing, reverse mortgages, the government-offered Pension Loans Scheme, and home reversion–type schemes) and reflects the current tax, superannuation, and age pension rules in Australia. We use state-of-the-art economic and actuarial modeling to identify the preferred approach for the use of housing wealth by Australian retirees with different marital status, wealth portfolios, and preferences. Chapter 4 uses an online experimental survey administered to a representative sample of Australian (pre-)retiree homeowners to explore whether information framing to address mental accounting and narrow choice bracketing can enhance the demand for reverse mortgages. The information framing to address mental accounting significantly increases the stated demand for reverse mortgages. Chapter 5 presents the results of an online experimental survey administered to a representative sample of Chinese (pre-)retiree homeowners to investigate the demand for LTCI financed through home equity release. We find that access to home equity release products significantly increases the stated demand for LTCI and that the preferred approach is to use a reverse mortgage. Overall, the findings in this thesis confirm that retirees would benefit from using housing wealth to finance retirement. The results also identify approaches to reduce the gap between theoretical and actual demand for home equity release products. The findings provide evidence that government and private providers can use to address barriers to increasing interest in and take-up of home equity release products and to develop new products to enhance the utilization of housing wealth in retirement.

  • (2021) Hastings, Bradley
    Thesis
    Decades of research on organizational change and its leadership has explored the influence of leaders on change outcomes. Yet, despite this accumulated effort, the likelihood of success remains stubbornly low. This dissertation explores: how do leaders improve the likelihood of change success? Prior scholarship has examined this question from two perspectives. Change practice discussion describes change processes, the activities that enable change, with allied suggestions for leader engagement – how to lead change processes. Change leadership discussion studies leader attributes, aiming to identify and generalize those allied with success and, in doing so, provide guidance for leadership development. Addressing the leader-success challenge, scholars have identified two problems: (1) these two discussions lack integration – while it is difficult to talk about change leadership without inherently referring to a change process, the former discussion overlooks the available choices between change processes, and (2) the study of attributes has yielded desired leader behaviors, yet evidence shows that these behaviors do not always manifest in practice. Addressing the first challenge, I commence with a process study of 79 cases of change. This research finds that a dynamic choice between two perspectives of change processes – illustrated as diagnostic and dialogic – significantly improves the likelihood of change success. It also extends an understanding of a leadership practice that facilitates this choice. Integrating these findings, I develop a model that explains how choice connects change leadership to change process knowledge, at the same time as providing a roadmap for leaders to navigate between diagnostic and dialogic processes in practice. Addressing the second challenge, psychologists explain a key limitation of behavioral study is that a large component of people’s behavior is a product of situational cues. To explain this phenomenon, these scholars have explored mindsets, describing how behavioral dispositions result from mental frameworks that stand ‘ready to fire’ based on situational cues. My second study establishes psychology-derived mindsets as relevant for leadership engagement of change processes. It does so by developing a typology of mindset constructs, then conducting an integrative review of mindset knowledge between change leadership and psychology settings. This study matches the fixed and growth mindsets with leadership engagement of diagnostic and dialogic change processes. My third study empirically examines how the fixed and growth mindsets manifest within leaders when change is targeted. It finds that leaders with a growth mindset are likely to choose to oscillate between change processes and achieve change success. Further, I identify that diagnostic change processes can provide situational cues that foster a fixed mindset within leaders, with detrimental effects on outcomes. Integrating these findings from all three studies, this dissertation puts forward a new means for leadership development – mindset activation theory – explaining a means for leaders to take control of their situation-mindset interaction and guide their behaviors in practice. It demonstrates how leaders can increase awareness of and operationalize the situational cues that guide their mindset, facilitating choices between change processes that improve their likelihood of change success.

  • (2021) Hickey, Nicole-Anne
    Thesis
    For decades scholars have detailed the benefits of having embedded workers in the workplace. Increasing embeddedness reduces the costs workplaces incur from workers’ withdrawal behaviours. In comparison, less is known regarding the costs of high embeddedness. Drawing on conservation of resource theory, this thesis examines the negative effects of embeddedness in conjunction with work role overload on burnout and withdrawal. It further considers the impact of workers’ physical and psychological maintenance of barriers between work and life (i.e., work-life boundary control flexstyles) on the aforementioned effects. The results of two waves of survey data from 243 aged care workers, analysed using a moderated mediation framework, showed work role overload and flexstyle moderate the mediated relationship between job embeddedness, burnout, and withdrawal behaviours (lateness, absenteeism, and turnover). These results underscore the importance of workers’ experience of work overload and their work-life control flexstyles when considering the impact of embeddedness on retaining, expanding, and sustaining the aged care workforce. These findings have important implications for employees, managers, and organisations in the aged care industry.

  • (2021) Wan, Cheng
    Thesis
    This thesis studies several important issues for ageing populations in developing countries facing basic public provisions of health services and pensions and high levels of air pollution. In particular, I investigate the demand for longevity, critical illness insurance (CII), and long-term care insurance (LTCI) in developing countries from both theoretical and empirical perspectives. I also study how PM2.5 (particles less than 2.5 micrometres in diameter) affects multimorbidity, cognition, and disability in activities of daily living (ADL) that are important health indicators for the old. The results provide insights into the design and risk management of retirement insurance products and government policies. First, we conduct an online experimental survey to elicit and analyse preferences for retirement portfolio including longevity, CII, and LTCI products after the COVID-19 pandemic outbreak in urban China. We observe a high variation of insurance demand by individual factors and COVID-19 experience, and their effects can be opposite by health-contingent insurance and life annuity. On average, the most preferred retirement portfolio contains health-contingent insurance that covers half of the expected out-of-pocket (OOP) costs for critical illness and long-term care expenditures, a monthly annuity of 20% of the disposable income. The portfolio that covers half of the OOP cost for long-term care, critical illness, or both, is most effective in increasing annuitisation. Next, we derive the optimal portfolio for retirees in China facing uncertain lifespan, catastrophic medical expenditures, and long-term care costs. An optimal portfolio highly depends on a retiree’s economic background. For a retiree with an average pension, we find that at least 30% of retirement wealth is allocated to CII, while at least 40% is allocated to a life annuity for those with a low pension. The demand for LTCI is less than 15% of retirement savings. State-dependent utility and bundled insurance products can both increase annuity demand for some retirees. Finally, we investigate the long-term impact of exposure to PM2.5 on multimorbidity, cognition, and ADL disability for the middle- and old-aged adults in China. We find different non-linear associations between PM2.5 exposure and the three health outcomes, and we also observe different impacts of past and current exposure to PM2.5 on them. We interpret the risk of PM2.5 exposure by comparing it to the effects of ageing.

  • (2022) Feng, Yang
    Thesis
    The stochastic optimal decision-making problem concerns the process of dynamically deciding actions to optimize pre-specified criteria based on specific stochastic models. It is, however, common that a decision-maker is unable to obtain complete information to formulate fully reliable models and faces the issue of model uncertainty. Existing empirical studies have shown that ignoring model uncertainty leads to improper decisions and causes losses in the financial market. Thus, it is important to incorporate model uncertainty into decision-making. To our best knowledge, no existing works on dividend optimization have taken model uncertainty into consideration. This thesis is an early attempt to fill such a gap in the actuarial literature. This thesis studies three popular optimization problems in the framework of model uncertainty, which involve different models with multiple control variables and various assumptions. It consists of three projects. The first project investigates an optimal risk exposure-dividend control problem under a diffusion model with model uncertainty. Due to the concerns about model uncertainty, the ambiguity averse insurer aims at finding the robust strategies such that a penalized reward function is maximized in the worst-case scenario. The problem is formulated as a zero-sum stochastic differential game between the insurer and the market. Explicit expressions for the value functions are obtained and the optimal dividend strategies are identified as barrier strategies. The second project incorporates model uncertainty into a dividend optimization problem of a singular type under the classical risk model with general assumptions on the claim size distribution. Using the standard stochastic control techniques, we characterize the value function as the smallest viscosity supersolution to the existing Hamilton-Jacobi-Bellman equation and show that the optimal strategies are of band type. The third project extends the second project by incorporating fixed and proportional transaction costs on dividend payments. The problem is an impulse control problem and the optimal dividend strategies are shown to be n-level lump sum strategies. Numerical studies are provided for each project and the economic implications of model uncertainty on insurer’s decision-making are discussed. It is shown that the insurer who is more averse to ambiguity tends to be more conservative in the optimal strategies.

  • (2021) Tian, Wei
    Thesis
    In Chapter 1, we provide conditions for the synthetic control estimator to be asymptotically unbiased when the outcome is nonlinear, and propose a flexible and data-driven method to choose the synthetic control weights. In the empirical application, we illustrate the method by estimating the impact of the 2019 anti-extradition law amendments bill protests on Hong Kong's economy, and find that the year-long protests reduced real GDP per capita in Hong Kong by 11.27% in the first quarter of 2020, which was larger in magnitude than the economic decline during the 1997 Asian financial crisis or the 2008 global financial crisis. In Chapter 2, we generalise the conventional synthetic control method to a multiple-outcome framework, where the time dimension is supplemented with the extra dimension of related outcomes. As a result, the synthetic control method can now be used even if only a small number of pretreatment periods are available or if we worry about structural breaks over a longer time span. We show that the bound on the bias of the multiple-outcome synthetic control estimator is of a smaller stochastic order than that of the single-outcome synthetic control estimator, provided that the unit of interest can be closely approximated by the synthetic control in terms of the observed predictors and the multiple related outcomes before the treatment. In the empirical application, we illustrate our method by estimating the effects of non-pharmaceutical interventions on various outcomes in Sweden in the first 3 quarters of 2020. Our results suggest that if Sweden had implemented stricter NPIs like the other European countries by March, then (1) there would have been about 70% fewer cumulative COVID-19 infection cases and deaths by July, and 20% fewer weekly deaths from all causes in early May; (2) temporary absence from work would increase by 76% and total hours worked would decrease by 12% among the employed in the second quarter, but the impact would vanish in the third quarter, and there would be no discernable effect on the employment rate throughout; (3) the volume of retail sales would shrink by 5%-13% from March to May, while the other economic outcomes including GDP, import, export, industrial production, and CPI would not be affected. In Chapter 3, we propose a method based on the interactive fixed effects model to estimate treatment effects at the individual level, which allows both the treatment assignment and the potential outcomes to be correlated with the unobserved individual characteristics. This method is suitable for panel datasets where multiple related outcomes are observed for a large number of individuals over a small number of time periods. To illustrate our method, we provide an example of estimating the effect of health insurance coverage on individual usage of hospital emergency departments using the Oregon Health Insurance Experiment data.

  • (2022) Herse, Sarita
    Thesis
    As collaborative agents are implemented within everyday environments and the workforce, user trust in these agents becomes critical to consider. Trust affects user decision making, rendering it an essential component to consider when designing for successful Human-Agent Collaboration (HAC). The purpose of this work is to investigate the relationship between user trust and decision making with the overall aim of providing a trust calibration methodology to achieve the goals and optimise the outcomes of HAC. Recommender systems are used as a testbed for investigation, offering insight on human collaboration with dyadic decision domains. Four studies are conducted and include in-person, online, and simulation experiments. The first study provides evidence of a relationship between user perception of a collaborative agent and trust. Outcomes of the second study demonstrate that initial trust can be used to predict task outcome during HAC, with Signal Detection Theory (SDT) introduced as a method to interpret user decision making in-task. The third study provides evidence to suggest that the implementation of different features within a single agent's interface influences user perception and trust, subsequently impacting outcomes of HAC. Finally, a computational trust calibration methodology harnessing a Partially Observable Markov Decision Process (POMDP) model and SDT is presented and assessed, providing an improved understanding of the mechanisms governing user trust and its relationship with decision making and collaborative task performance during HAC. The contributions from this work address important gaps within the HAC literature. The implications of the proposed methodology and its application to alternative domains are identified and discussed.

  • (2022) Faulkner, Anne
    Thesis
    Policy capacity implies the presence of a range of individual skills, work activities and organisational abilities that combine to facilitate high-level performance of the policy function in an organisation. In the context of increasingly complex public policy issues and processes, high-level policy capacity is a key objective for public sector development in Australia and internationally. Since the late 1970s, several administrative reviews have assessed the ability of the Australian Public Service (APS) to meet the demands of a changing and increasingly complex public governance environment. Policy capacity has persistently been identified as an area for improvement in these reviews, resulting in repeated attempts to address deficiencies. Why APS policy capacity has failed to improve despite these attempts is unclear; however, persistent negative assessments of APS policy capacity suggest a failure of reformers to identify critical obstacles to the development of policy capacity in the APS environment. The importance of policy capacity to policy performance necessitates clarifying how the conditions for effective policy capacity can be shaped by environmental factors and how conditions might be engineered for improved performance. This study considers these issues through examination of policy capacity in APS social policy agencies. Performance and accountability instruments are key tools for establishing performance and behaviour in an institutional setting and have acted as key tools for reform of policy performance within the APS. However, how performance and accountability instruments determine the level of policy capacity in the APS environment, how policy capacity is built and the influence of contextual factors on policy capacity remain under-examined, implying some assumptions underlying past reforms of these instruments are untested. Performance and accountability instruments, like all administrative instruments, must meet multiple objectives in their implementation including administrative functionality and political ideological objectives. Those designed since 1980 are likely to have New Public Management (NPM) objectives at their core, such as efficiency and effectiveness, avoiding risk and performance measurement. However, these may be at odds with other objectives for policy work, such as the development of specialist skills, power-sharing, working across portfolios and systems, and working closely and responsively with the public. Social policy work objectives, in particular, can be hard-to-measure social wellbeing objectives that require working in ways that may be challenging for administrative efficiency such as working in consultative and inclusive ways and across multiple portfolios and their policy settings To examine policy capacity in APS social policy agencies, this exploratory study employs qualitative methods for content analysis of key APS performance and accountability documents and thematic analysis of interviews with APS social policy workers. The research framework is underpinned by critical realist principles and institutional theories. This study shows that while the APS performance and accountability framework builds social policy staff knowledge about policy capacity, it fails to enable social policy through an effective combination of hard and soft structures. This thesis argues that this failure to structure appropriately for policy capacity derives from competition between core expectations in the politico-administrative environment regarding the APS’ role in policy work and visions of policy capacity, suggesting that policy capacity is unrealistic in certain political and administrative systems. This argument suggests that policy capacity can face an uphill battle against the competing demands of political and administrative settings, even as the concept of policy capacity becomes more entrenched as desirable in academic and public sector discourse. This study contributes knowledge about building policy capacity, how context influences policy capacity and how performance and accountability instruments contribute to policy capacity, this study confirms principles in the extant public administration and institutional literature on the functioning and efficacy of administrative frameworks and NPM tools in shaping behaviour, knowledge, performance. The study also contributes new knowledge to the policy capacity and public administration literature regarding a concept of social policy capacity, how different types of performance and accountability structures shape the potential for policy capacity and can inform structural planning principles for developing policy capacity, and the influence of the politico-administrative context on policy capacity.

  • (2022) Yang, Yu
    Thesis
    Research in computational statistics develops numerically efficient methods to estimate statistical models, with Monte Carlo algorithms a subset of such methods. This thesis develops novel Monte Carlo methods to solve three important problems in Bayesian statistics. For many complex models, it is prohibitively expensive to run simulation methods such as Markov chain Monte Carlo (MCMC) on the model directly when the likelihood function includes an intractable term or is computationally challenging in some other way. The first two topics investigate models having such likelihoods. The third topic proposes a novel model to solve a popular question in causal inference, which requires solving a computationally challenging problem. The first application is to symbolic data analysis, where classical data are summarised and represented as symbolic objects. The likelihood function of such aggregated-level data is often intractable as it usually includes a high dimensional integral with large exponents. Bayesian inference on symbolic data is carried out in the thesis by using a pseudo-marginal method, which replaces the likelihood function with its unbiased estimate. The second application is to doubly intractable models, where the likelihood includes an intractable normalising constant. The pseudo-marginal method is combined with the introduction of an auxiliary variable to obtain simulation consistent inference. The proposed algorithm offers a generic solution to a wider range of problems, where the existing methods are often impractical as the assumptions required for their application do not hold. The last application is to causal inference using Bayesian additive regression trees (BART), a non-parametric Bayesian regression technique. The likelihood function is complex as it is based on a sum of trees whose structures change dynamically with the MCMC iterates. An extension to BART is developed to estimate the heterogeneous treatment effect, aiming to overcome the regularisation-induced confounding issue which is often observed in the direct application of BART in causal inference.

  • (2021) Jiang, Yuchao
    Thesis
    Support from peers and experts, such as feedback on research artefacts, is an important component of developing research skills. The support is especially helpful for early-stage researchers (ESRs), typically PhD students at the critical stage of learning research skills. Currently, such support mainly comes from a small circle of advisors and colleagues. Gaining access to quality and diverse support outside a research group is challenging for most ESRs. This thesis presents several studies to advance the fundamental and practical understanding of designing systems to scale support for research skills development for ESRs. First, we conduct a systematic literature review on crowdsourcing for education that summarizes existing efforts in the research and application domain. This study also highlights the need for studies on crowdsourcing support for research skills development. Then, based on findings from the first study, we conducted another systematic literature review study on crowdsourcing support for project-based learning and research skills development. The third study explores the qualitative empirical understanding of how ESRs leverage current socio-technical affordances for distributed support in their research activities. This study reveals opportunities afforded by socio-technical systems and challenges faced by ESRs when seeking and adopting support from online research communities. The fourth study explores quantitative empirical understandings of the most desired types of feedback from external researchers that need to be prioritized to offer, and the challenges that need to be prioritized to solve. Building on the findings from the four studies above, we proposed a theoretical framework -- Researchersourcing -- that guides the understanding and designing of socio-technical systems that scale the support for research skills development. Accordingly, in the fifth study, we design and evaluate a crowdsourcing pipeline and a system to scale feedback on research drafts and ease the burdens of reviewing research drafts.