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(2021)ThesisMarketers increasingly recognize that consumer decisions may be ascribed to emotional motivations. While several scholars have examined the influence of discrete negative and positive emotions in consumption contexts, one emotion that has been understudied in marketing is the influence of the emotion of awe. Awe is a positive emotion elicited by extensive or vast stimuli, either perceptually or conceptually, which leads to the revision of mental schemas. Further, as a self-transcendent, other-focused emotion, awe has properties that suggest its potential in driving consumer well-being. The central insight of this thesis is that awe and related states like threat-awe can have unique influences on consumer behaviour. For instance, prior research has argued threat-awe as a negative-valenced variant of awe that would prime similar downstream consequences as awe. Contrastingly, the first essay, “The Curious Case of Threat-Awe”, conceptualizes threat-awe as a mixed emotion of awe and fear, rather than a negative-valenced state. Over five studies, we draw on two methodologies - cognitive appraisals and an index of bivalence - and elucidate how threat-awe’s appraisal profile, valence, and behaviour (risk-taking) are distinct from univalenced emotions like awe and fear. The second essay, “Feeling Small but Thinking Big”, conceptualizes awe's positive self-diminishment effect and develops a framework of how awe facilitates engagement in sustainable consumption. Across four studies, this essay demonstrate how awe positively impacts consumers’ willingness to pay for sustainable products. The essay further shows the underlying sequential mechanism of positive self-diminishment and examines boundary conditions of product packaging and product type. In the final essay, “Betting on Myself”, we show that the positive self-diminishment effect of awe reduces financial risk-taking in the domain of gambling. Using multiple methodologies to prime awe (writing/reading task, virtual reality), we compare awe against other positive emotions such as pride, happiness, amusement, and neutral, and demonstrate that awe-induced self-diminishment reduces gambling tendency. The studies also rule out several alternative explanations and examine the boundary condition of feedback on performance. Overall, across the three essays, this thesis highlights socio-cognitive engagement of awe and its behavioural consequences relevant to consumer decisions and well-being.
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(2021)ThesisThis thesis consists of three chapters that investigate the linkage between uncertainty and corporate investment decisions on an international basis. In first chapter, I investigate the extent of U.S. policy-related spillovers into 22 other real economies. I find that, after accounting for factors previously used to explain corporate investment, US Economic Policy Uncertainty (US EPU, hereafter) fluctuations affect foreign corporate investments through two channels. First, the single effect of US EPU on international corporate investment shows an unequivocal negative relation (the direct channel). Second, an increase in US EPU also attenuates the negative sensitivity of corporate investment towards the cost of capital (the indirect channel). Further, I find that while the direct channel of US EPU on corporate investment persists across several subsamples, its indirect channel relates to a high degree of dependence on the U.S. economy and opacity exhibited by local economies. The second chapter reconciles the contrary views on the foreign investors using local disaster shocks from 46 countries over the period 1998-2018. I find that local disaster shocks cause significant disruptions to corporate investments, but foreign institutional investors attenuate the costs of disaster risks. The benefits associated with foreign institutional investors are not uniformly held across all economies, where the role of foreign institutional investors is particularly measurable in countries with well-developed institutional environment. The third chapter focuses on the uncertainty at domestic level using national elections across 23 different countries. I find that the corporate investment cycle corresponds with the timing of national elections, but there is a cross-sectional difference in the firm-level investment sensitivity to elections. During election periods, while firms temporarily reduce investment expenditures relative to nonelection years, the decline is mainly sourced from firms with greater political exposures. Further, I find that the investment cycles are more volatile when the election outcomes are uncertain, and the institutional environments are weaker.
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(2022)ThesisThis dissertation consists of three essays on asset pricing and market microstructure topics within the U.S. corporate bond market. The first essay investigates asymmetry in price pressure between customer buy and sell orders and demonstrates that it is a valuable measure of downside liquidity for corporate bonds. While evidence of a characteristic premium for illiquidity in the cross-section of corporate bonds is mixed, aggregate liquidity asymmetry has high explanatory power for the time series of market returns. Its statistical and economic significance justify it as a credible asset pricing factor. Average market-wide liquidity asymmetry comoves with interest rate and credit spread changes, investor sentiment, funding liquidity, dealer inventory, exchange-traded fund flows, and post-crisis regulatory change. The second essay documents the properties of market-wide corporate bond liquidity and demonstrates that liquidity risk is an important determinant of returns. In market downturns, transaction costs rise for sellers and fall for buyers. The negative relation between buyer and seller liquidity motivates a new across-measure liquidity factor that incorporates an asymmetric liquidity component. Shocks to market-wide liquidity explain a large portion of bond return variation in the time series. Primarily driven by the asymmetric component, the liquidity factor attracts a cross-sectional risk premium that is robust to controls for credit, equity, and interest rate factors, as well as the illiquidity level. The third essay provides new evidence of retail investors’ ability to predict returns based on transactions in U.S. corporate bonds with equity-like risk. Retail order flow is persistent and contrarian, and it predicts future returns in the cross-section. The profits of an equal-weighted, long-short strategy that buys (sells) bonds that experience high (low) net retail buying are economically meaningful. The alpha based on decile portfolios is significant at the 10% level when controlling for common equity and bond risk factors. However, due to high transaction costs and because retail purchase volume is concentrated in underperforming bonds, retail traders lose money in aggregate.
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(2022)ThesisAs chatbots are deployed for service interactions with customers on the organizational frontline, they are designed to be humanlike (anthropomorphized) to increase acceptance and usage. Although the use of chatbots continues to rise, there is a lack of guidelines on effective chatbot design and its impact on customer responses. Drawing from social cognitive theory (SCT) and stereotype content model (SCM), this thesis consists of three essays that theoretically propose and empirically test the underlying mechanisms of the effect of embodied conversational agent (ECA, a form of chatbot with digital face/head or body) design on customer outcomes. Essay 1 (Chapter 2) conceptualizes three aspects of ECA design (i.e., anthropomorphic role, appearance and interactivity) and presents a framework on how they impact service outcomes by influencing people's agency. Essay 2 (Chapter 3) builds on Essay 1 and introduces ‘value-by-proxy’ as a two-stage process that accounts for how the three anthropomorphic affordances relevant to ECAs (i.e., anthropomorphic role, visual appearance and conversational style) translate into relevant customer outcomes in the delivery of online financial coaching service. The essay uses an experimental approach that simulates an interactive service encounter with an ECA and incorporates implementation intentions with regard to (non)use and advice compliance, which is integrated with a Gabor Granger study to assess the willingness to pay. Based on a sample of 596 US-based respondents recruited from a Prolific panel, the results provide evidence on the serial mediation of the impact of anthropomorphic affordances on customer outcomes. Essay 3 (Chapter 4) conceptually and empirically explores how the dimensions of warmth and competence are afforded through prosody (enthusiastic vs. calm voice) and interaction styles (socioemotional vs. task-focused) in establishing perceptions of virtual rapport and in turn customer usage and compliance intentions. Data were collected from two studies: 390 US-based respondents recruited from a Prolific panel participated in an online experiment in Study 1, and 212 US-based respondents from a Conjoint.ly panel participated in a choice-based conjoint experiment in Study 2. The findings demonstrate a process of moderated serial mediation such that feelings of rapport are driven by believability and that this relationship is enhanced by a willingness to suspend disbelief.
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(2022)ThesisData-driven decision making is everywhere in the modern sporting world. The most well-known example of this is the Moneyball movement in Major League Baseball (MLB), which built on research by Sherri Nichols in the 1980s, but sport analytics has also driven major changes in strategy in basketball, the National Football League, and soccer. In Australia, sports analytics has not had quite the same influence in its major domestic codes. In this thesis, we develop tools to assist the analytics community in two major Australian commercial sports. For Australian Rules Football, the largest commercial sport in Australia, data was not readily accessible for the national competition, the Australian Football League (AFL). Data access is fundamental to data analysis, so this has been a major constraint on the capacity of the AFL analytics community to grow. In this thesis, this issued is solved by making AFL data readily accessible through the R package fitzRoy. This package has already proven to be quite successful and has seen uptake from the media, fans, and club analysts. Expected points models are widely used across sports to inform tactical decision making, but as currently implemented, they confound the effects of decisions on points scored and the situations that the decisions tend to be made in. In Chapter 3, a new expected points approach is proposed, which conditions on match situation when estimating the effect of decisions on expected points. Hence we call this a conditional Expected Points (cEP) model. Our cEP model is used to provide new insight into fourth Down (NFL) decision-making in the National Football League, and decision-making when awarded a penalty in Rugby League. The National Rugby League (NRL) is the leading competition of Australia’s second largest commercial sport it is played on a pitch that is 100m long and 70m wide, and the NRL have provided us with detailed event data from the previous five seasons, used in academic research for the first time in this thesis. We found that NRL teams should kick for goal from penalties much more often than is currently the case. In Chapter 4 we develop a live probability model for predicting the winner of a Rugby League game using data that is collected live. This model could be used by the National Rugby League during broadcasts to enhance their coverage by reporting live win probabilities. While most live probability models are constructed using scores only, the availability of live event data meant we could investigate whether models constructed using event data have better predictive performance. We were able to show that in addition to score differential that the addition of covariates such as missed tackles can improve the prediction. Clubs use their own domain knowledge to test their own live win probability theories with the R scripts that are provided to the NRL
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(2022)ThesisDigital work exemplifies the impact of Information Systems (IS) on everyday life in the modern world. Digital nomadism is an extreme incarnation of digital work, entailing knowledge workers mobilising — from fixed life and work arrangements in one place, to a lifestyle of travel and mobile, location-independent work — facilitated by digital technologies. Many see digital nomadism as a promising alternative to entrenched patterns in society, particularly in how workers relate to organisations and how citizens relate to nation states. However, others may critique and question digital nomadism for its shortcomings and ethical issues. This thesis engages with this fragmented discourse on digital nomadism by making contributions through the lens of critical theory. As this thesis outlines, critical theory is an intellectual tradition that sensitises scholars to critical-theoretic perspectives: Empowerment and Emancipation; Exploitation and Marginalization; Systems and Structures; Agency and Technology; Environment and Sustainability; Ethics and Morality. This thesis is comprised of four related papers. The first paper presents an overview of different types of theorising in critical-theoretic IS research, revealing a diverse philosophical landscape of intellectual foundations that can help scholars make sense of the interplay between critical-theoretic issues and IS phenomena like digital nomadism. The second paper then leverages the findings of the first paper, to present a literature review of digital nomadism from a critical theory perspective. The second paper reveals that critical-theoretic knowledge claims are already visible in the scholarly literature on digital nomadism but have yet to be fully understood, thus suggesting the need for future research. Based on this foundational understanding of the literature on digital nomadism and the literature on critical-theoretic IS research, the third and fourth papers make contributions based on empirical findings from fieldwork in major digital nomad destinations. The third paper employs the empirical findings to envision the future of post-COVID-19 knowledge work, based on a Hegelian dialectical perspective; and the fourth paper employs the empirical findings to reveal how digital nomadism entails an avenue for achieving workers’ emancipation that constitutes a departure from the traditional conceptualisation of emancipation in the nation state.
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(2022)ThesisThe overall aim of this thesis is to provide a comprehensive understanding of customer acceptance of frontline service robots (FSR). To achieve this goal, three underpinning research objectives were first generated: (1) to develop and empirically examine a model of customer acceptance of FSR; (2) to investigate how customers evaluate and accept FSR in a service failure context; and (3) to examine potential moderators that may change the nature of the relationship in the empirical models. This thesis consists of three stand-alone studies that collectively contribute to understanding customer acceptance of FSR, as well as providing insightful managerial implications. The first study qualitatively explores the underlying factors that customers consider regarding FSR acceptance based on their interaction experiences with an FSR in a retail banking context. The results identified 16 dimensions, grouped into five main themes: the utilitarian aspect, social interaction, customer responses towards FSR, customer perspectives of the company brand, and individual and task heterogeneity. These provided initial evidence with which to develop a comprehensive FSR acceptance model. Drawing on self-determination theory (SDT), Study 2 developed and empirically tested a model of FSR acceptance as a function of the fulfillment of basic human needs. It revealed that FSR can provide psychological comfort by meeting functional and hedonic evaluations (i.e., functionality and enjoyment), that in turn lead to customer willingness to accept the technology. Additionally, implementing FSR can enhance customer perception of a firm’s innovativeness. The need for human interaction was also found to be a moderating variable that strengthens the effect of perceived sociability and social presence on customer evaluation of FSR functionality. Lastly, Study 3 – anchored in attribution theory and the concept of automated social presence – examined customer acceptance of FSR in a service failure context. The results showed that an internal (rather than external) locus of attribution and high social presence displayed by FSR produces a more positive evaluation of FSR functionality and psychological comfort, even when customers experience a service failure incident. Additionally, the findings suggest that perceived failure severity moderates the link between the locus of attribution and customer evaluation of FSR functionality, and psychological comfort.
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(2022)ThesisUsing the VC industry as a laboratory, we investigate whether incidental in-person interactions between people working in close proximity facilitate their future collaboration on projects of significant economic value. Our analysis exploits urban topological features surrounding VC fund offices that generate exogenous variations in the likelihood of incidental in-person interactions. We show that such variations influence syndicate partner choice among VCs within narrowly defined (walkable) geographic zones. Workplace smoking bans affecting social smoking appear to reduce such effects. Weather patterns that exogenously restrict VC fund managers’ outdoor activity are also shown to moderate the role played by incidental encounters. Our results cannot be explained by VCs’ characteristics, prior relationships, and portfolio firms’ locations. Finally, syndicated deals driven by in-person interactions do not appear to generate superior returns.
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(2023)ThesisMortality modelling and projection is important for actuarial science and significant amount of research has been done in this regard. In addition to the systematic uncertainty over time, mortality risk can also vary across individuals of the same age, a phenomenon known as mortality heterogeneity. In this thesis, I propose and establish a mortality model incorporating health heterogeneity, based on which I assess the positive impact of considering health effects on both government and individual retirement finances. I also incorporate systematic mortality by health state and extend the estimation of cohort mortality models to incomplete cohort data. In cohort mortality modelling, the traditional Kalman Filter Algorithm (KFA) uses the complete older cohort data while ignoring the recent incomplete cohort data. The calibrated mortality model can lead to unreliable mortality projections especially for long-term projections. In the first part of the thesis, I extend the traditional KFA by incorporating recent incomplete cohort data in the model fitting process, ensuring the mortality model projection is more accurate and better captures cohort mortality developments. Then in the second part, I propose and estimate a finite-state Markov Ageing Model (MAM) incorporating health heterogeneity, which is calibrated based on Australian cohort mortality and health condition data. This model better captures both the mortality and health developments for individuals with different initial health status. We capture the feature that healthier individuals are more likely to survive, while less healthy individuals are more likely to die based on the calibrated model. Allowing for health heterogeneity when make retirement planning is important because of these differences. In the last part, I provide an impact analysis of the MyRetirement system (CIPRs) from two perspectives: first, I use the multi-state health mortality model with which we consider both systematic mortality and health heterogeneity. Second, I add health-linked components (deferred health annuities) to the CIPRs' portfolio framework, aiming to provide health-linked income streams for retirees when their health costs increase significantly. I show how this extension is beneficial both to the government, in terms of Age Pension payments, and to retirees, in terms of retirement incomes.
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(2022)ThesisThis thesis seeks to produce new methods for the analysis and prediction of counting processes through the usage of Markov-modulated non-homogeneous Poisson processes. The modelling framework was motivated by problems arising in general (non-life) insurnace but the developed techniques are applicable to a variety of different modelling contexts although specific innovations are implemented to deal with large data sources. An important issue dealt with in this thesis is that in many real world circumstances, it is often the case that the practitioner is able to rely on some domain knowledge or past experience to inform the modelling process. However, it is also unlikely that all drivers of events of interest are able to be adequately captured by a practitioner's chosen model due to data limitations and materiality concerns. The proposed modelling framework serves to link the modellable factors (allowing much flexibility in terms of model choice) with unmodellable/hard-to-model factors through the use of a hidden Markov structure. The separation of these two components provides advantages in terms of adaptability, interpretability and realism. Further, the model may also be utilised as a diagnostic/performance evaluation tool for the practitioner's chosen model and also for iterative model improvement. This thesis further produces a model calibration algorithm through the use of an Expectation-Maximisation procedure. Several improvements are made to enhance the practicability of the calibration by severely reducing computational requirements while allowing the procedure to be run on standard statistical software such as R. Additionally, both simulated and real world empirical demonstrations are provided to highlight that the out-of-sample predictions generated by this approach can produce superior forecast distributions compared to standard methods in practice. Finally, a computationally feasible method to generate parameter error estimates is developed to to assess the uncertainty of the model. Computational considerations are particularly necessary with large data sets where latent models such as the MMNPP provide value. This approach is shown to provide more realistic and distributionally accurate out-of-sample predictions. The benefits of this assessment are demonstrated using simulated and real data case studies which provide evidence of the advantages of incorporating parameter error considerations under the MMNPP framework.