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Submitted in total fulfilment of the requirements for the degree of Master of Science to the School of Psychology and Public Health, La Trobe University, Victoria, Australia.

A thesis submitted in total fulfilment of the requirements for the degree of Doctor of Philosophy to the Australian Research Centre for Sex, Health and Society, School of Psychology and Public Health, La Trobe University, Victoria, Australia.

Background Hysterectomy is a common procedure worldwide and removing healthy fallopian tubes at the time of hysterectomy (opportunistic salpingectomy) to possibly prevent ovarian cancer is increasing in frequency, but still controversial. The experiences and perceptions of women, eligible for the procedure, have not been previously investigated. This study aims to, among women waiting to undergo hysterectomy, explore i) experiences and perceptions of self and healthcare in relation to their elective surgery, ii) perceptions of risks and benefits of hysterectomy, including opportunistic salpingectomy. Methods A qualitative study, with focus group discussions including women Results Twenty-one Swedish-speaking women participated. They were 40–53 years of age, reported varying educational levels, countries of birth and indications for hysterectomy. Analysis rendered a theme “Bridging different realities” over four categories: “Being a woman today”, “Experiencing and managing body failure”, “Navigating the healthcare system” and “Processing continuously until surgery”, including 17 subcategories. The participants displayed varying attitudes towards the significance of their uterus in being a woman. A vague understanding of their body was described, leading to fear related to the reasons for surgery as well as surgery itself. Participants described difficulties understanding and recalling information but also stated that insufficient information was provided. Perceptions of the risks and benefits of opportunistic salpingectomy varied. Involvement in decisions regarding the hysterectomy and potential opportunistic salpingectomy was perceived to be dependent on the counselling gynecologist. Conclusions The theme Bridging different realities captures the complexity of women deciding on removal of their uterus, and possibly fallopian tubes. It also describes the women’s interactions with healthcare and perceived difference between the health professionals and the women’s perception of the situation, as viewed by the women. Bridging the different realities faced by patients is required to enable shared decision-making, through sufficient support from healthcare.

A thesis submitted in total fulfilment of the requirements for the degree of Master of Arts to the School of Humanities and Social Sciences, La Trobe University, Victoria, Australia.

The purpose of this research was to evaluate the police recruit selection process in the Queensland Police Service. The- process was introduced for the February 1991 intake of recruits undertaking a new university - based pre -service Recruit Training Program.The research includes a literature review of the different selection techniques used in personnel selection generally and police selection, specifically. These are past education achievement, psychometric assessments, selection interviews, community inquiry, physical and medical assessments, and personal integrity. Personal integrity wasassessed through the community inquiry and criminal and traffic history checks.The emphasis of the research was on those selection techniques which are not pass/fail, that is, education achievement, psychometric assessments and selection panel interview, and the ability of these to predict levels of achievement during police training.The data analysis involved gathering information on two groups of recruits, from the time of their application until the end of the Pre -Service Program. A multiple regression analysis was conducted on the two sets of data. Cross -validation of results was the purpose of the study.The criterion measure for this analysis was total grades achieved during the two semester program. The assumption of this research was that the training undertaken was job -related. Criteria which predict training success should therefore predict job success. Support was found for the following hypotheses:1. There will be a significant positive correlation between results on psychometric assessments and results in the Recruit Training Program at the Queensland Police Academy.2. There will be a significant positive correlation between education achievement and results of the Recruit Training Program.3. The selection process used does not unlawfully discriminate against people with different cultural backgrounds relative to the requirements of the job.The third hypothesis was addressed through the literature review as no information was available as to the cultural backgrounds of the recruits being studied.

A thesis submitted in total fulfilment of the requirements for the degree of Doctor of Philosophy to the Department of Psychology, School of Behavioural Sciences, La Trobe University, Bundoora, Victoria, Australia.

The distinguishing feature of all great leaders throughout history has been that they inspire ���hope���. But where is it exactly?

Our research aims to understand learning and decisions from experience in dynamic decision environments. Our work relies on a theory of learning from experience called Instance-Based Learning Theory (IBLT) and on other theories and ideas, mostly from cognitive psychology. Dynamic Decision Making Laboratory poster, April 2022

Sequential decision-making is a fundamental class of problem that motivates algorithm designs of online machine learning and reinforcement learning. Arguably, the resulting online algorithms have supported modern online service industries for their data-driven real-time automated decision making. The applications span across different industries, including dynamic pricing (Marketing), recommendation (Advertising), and dosage finding (Clinical Trial). In this dissertation, we contribute fundamental statistical design advances for sequential decision-making algorithms, leaping progress in theory and application of online learning and sequential decision making under uncertainty including online sparse learning, finite-armed bandits, and high-dimensional online decision making. Our work locates at the intersection of decision-making algorithm designs, online statistical machine learning, and operations research, contributing new algorithms, theory, and insights to diverse fields including optimization, statistics, and machine learning. In part I, we contribute a theoretical framework of continuous risk monitoring for regularized online statistical learning. Such theoretical framework is desirable for modern online service industries on monitoring deployed model's performance of online machine learning task. In the first project (Chapter 1), we develop continuous risk monitoring for the online Lasso procedure and provide an always-valid algorithm for high-dimensional dynamic pricing problems. In the second project (Chapter 2), we develop continuous risk monitoring for online matrix regression and provide new algorithms for rank-constrained online matrix completion problems. Such theoretical advances are due to our elegant interplay between non-asymptotic martingale concentration theory and regularized online statistical machine learning. In part II, we contribute a bootstrap-based methodology for finite-armed bandit problems, termed Residual Bootstrap exploration. Such a method opens a possibility to design model-agnostic bandit algorithms without problem-adaptive optimism-engineering and instance-specific prior-tuning. In the first project (Chapter 3), we develop residual bootstrap exploration for multi-armed bandit algorithms and shows its easy generalizability to bandit problems with complex or ambiguous reward structure. In the second project (Chapter 4), we develop a theoretical framework for residual bootstrap exploration in linear bandit with fixed action set. Such methodology advances are due to our development of non-asymptotic theory for the bootstrap procedure. In part III, we contribute application-driven insights on the exploration-exploitation dilemma for high-dimensional online decision-making problems. Such insights help practitioners to implement effective high-dimensional statistics methods to solve online decisionmaking problems. In the first project (Chapter 5), we develop a bandit sampling scheme for online batch high-dimensional decision making, a practical scenario in interactive marketing, and sequential clinical trials. In the second project (Chapter 6), we develop a bandit sampling scheme for federated online high-dimensional decision-making to maintain data decentralization and perform collaborated decisions. These new insights are due to our new bandit sampling design to address application-driven exploration-exploitation trade-offs effectively.

'Will, preferences and rights’ is the new guiding principle for all support for or exercise of decision-making under the Convention on Rights of Persons with Disabilities, but its meaning is disputed and practice implications are poorly understood. This article explores key debates across disciplines and draws on grounded theory fieldwork findings to bring greater clarity to the principle within law, policy and practice settings. It is argued that the principle calls for a nuanced understanding which cautions against expectations that mere enactment into law or adoption within programs of support will prove to be a panacea.

Submitted in total fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Allied Health, Human Services, and Sport, College of Science, Health and Engineering, La Trobe University, Victoria, Australia.

Setting mechanical ventilation (MV) settings for ICU patients is a challenging task performed only by clinical specialists. Guidelines, experience, and intuition guide them. However, this ‘one-size-fits-all’ approach will benefit most but not all. Clinicians need to cater to the individual level and adjust settings proactively to improve the standard of care for respiratory failure patients. This thesis covers three major areas: the development of a decision support system protocol via model-based techniques to provide recommended MV settings, the development of a stochastic model of respiratory elastance, and finally, a virtual patient platform for rapid prototyping of developed MV protocols.

This thesis is submitted in total fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Psychology and Public Health, College of Science, Health and Engineering, La Trobe University, Victoria, Australia.

In our day to day lives, we are sometimes presented with information from two different channels of information, and sometimes this information can be incongruent. For example, if someone were to give directions and point left but say right instead. In situations such as these, which information channel do people rely on? To answer this question, we conducted two experiments. In Experiment 1, participants followed instructions from verbal and visual channels, that were sometimes incongruent, to move objects on their screens. In the first (training) block, probabilistic feedback either biased participants towards the verbal or the visual channel. The second (test) block contained no feedback. We found statistical learning of the bias in both verbal and visual conditions in the training block, although there was a stronger bias towards the verbal channel and much variability among participants. To investigate the origin of this variability, Experiment 2 removed feedback. Instead, participants completed two additional tasks: the Corsi Block and Digit Span tasks, which measure visual and verbal working memory, respectively. The results showed that people with higher visuospatial working memory showed less bias towards relying on the verbal channel. Collectively, these data suggest a bias towards prioritizing verbal information unless people have strong visuospatial working memory or the environment signals that the verbal channel is less reliable.

Consumers are negatively impacted by the increasingly high rate of product returns. In 2020, an estimated $428 billion in merchandise were returned to retailers post-purchase with $25.3 billion being fraudulent returns (NRF.com). Previous research has stated that consumers undergo various negative emotional and cognitive mechanisms when returning and identified reasons as to why consumers return purchases such as product failure, dissatisfaction, and regret (Lee, 2015). Specifically, regret occurs when an individual second-guesses a chosen product due to the realization that the benefits of the unchosen product outweigh the original choice, which elicits uncomfortable feelings (Zeelenberg et al., 1998). However, how does the process of product acquisition and the outcome of the purchasing decision affect post-purchase consumer regret? The purpose of this study is to investigate how the process of expending consumer resources (e.g., time vs. money) to acquire a product and the outcome of inconsistent product attitudes and behaviors (e.g., cognitive dissonance) can affect post-purchase consumer regret (PPCR). In this mixed factorial design, participants viewed scenarios that presented the ‘time’ and ‘money’ spent in acquiring their chosen product and were asked to read a product review that either elicited low or high dissonant feelings. It was hypothesized that consumers would experience greater PPCR when dissonance is high, and the time spent to acquire the product is primed. The interaction effect was not supported; however, an ad hoc analysis revealed that a consumer experienced less PPCR when dissonance is high, and the time spent to acquire the product is highly convenient. The current findings highlight the importance of understanding the process and outcome of purchase on post-purchase evaluations.

Submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy to La Trobe Business School, La Trobe University, Victoria.

Submitted in total fulfilment of the requirements for the degree of Master of Science to the Department of Computer Science and Information Technology, School of Engineering and Mathematical Sciences, College of Science, Health and Engineering, La Trobe University, Victoria.

An important aspect of making good decisions is the ability to adapt to changes in the values of available choice options, and research suggests that we are poor at changing behavior and adapting our choices successfully. The current paper contributes to clarifying the role of memory on learning and successful adaptation to changing decision environments. We test two aspects of changing decision environments: the direction of change and the type of feedback. The direction of change refers to how options become more or less rewarding compared to other options, over time. Feedback refers to whether full or partial information about decision outcomes is received. Results from behavioral experiments revealed a robust effect of the direction of change: risk that becomes more rewarding over time is harder to detect than risk that becomes less rewarding over time; even with full feedback. We rely on three distinct computational models to interpret the role of memory on learning and adaptation. The distributions of individual model parameters were analyzed in relation to participants’ ability to successfully adapt to the changing conditions of the various decision environments. Consistent across the three models and two distinct data sets, results revealed the importance of recency as an individual memory component for choice adaptation. Individuals relying more on recent experiences were more successful at adapting to change, regardless of its direction. We explain the value and limitations of these findings as well as opportunities for future research.

Once we have prioritised the behaviours we want to change, we can be tempted to jump straight to interventions, only to discover they haven’t worked as well as we would have hoped. In the end, our interventions might have targeted the wrong influences on behaviour based on some misplaced assumptions. In this chapter, which marks the beginning of the Deep Dive phase of the BWA Method, we introduce you to a practical synthesis of these influences on behaviour that will help remove the guesswork and misplaced assumptions of your behaviour change endeavours.

Post-disaster temporary housing has been a significant challenge for the emergency management group and industries for many years. According to reports by the Department of Homeland Security (DHS), housing in states and territories is ranked as the second to last proficient in 32 core capabilities for preparedness.The number of temporary housing required in a geographic area is influenced by a variety of factors, including social issues, financial concerns, labor workforce availability, and climate conditions. Acknowledging and creating a balance between these interconnected needs is considered as one of the main challenges that need to be addressed. Post-disaster temporary housing is a multi-objective process, thus reaching the optimized model relies on how different elements and objectives interact, sometimes even conflicting, with each other. This makes decision making in post-disaster construction more restricted and challenging, which has caused ineffective management in post-disaster housing reconstruction. Few researches have studied the use of Artificial Intelligence modeling to reduce the time and cost of post-disaster sheltering. However, there is a lack of research and knowledge gap regarding the selection and the magnitude of effect of different factors of the most optimized type of Temporary Housing Units (THU) in a post-disaster event. The proposed framework in this research uses supervised machine learing to maximize certain design aspects of and minimize some of the difficulties to better support creating temporary houses in post-disaster situations. The outcome in this study is the classification type of the THU, more particularly, classifying THUs based on whether they are built on-site or off-site. In order to collect primary data for creating the model and evaluating the magnitude of effect for each factor in the process, a set of surveys were distributed between the key players and policymakers who play a role in providing temporary housing to people affected by natural disasters in the United States. The outcome of this framework benefits from tacit knowledge of the experts in the field to show the challenges and issues in the subject. The result of this study is a data-based multi-objective decision-making tool for selecting the THU type. Using this tool, policymakers who are in charge of selecting and allocating post-disaster accommodations can select the THU type most responsive to the local needs and characteristics of the affected people in each natural disaster.

The BehaviourWorks Australia Method Book provides practitioners with a prioritised list of research and decision-making tools that will increase the chances that any behaviour change efforts will be effective. The Book is based on our extensive experience of applying different behaviour change skills and approaches in partnership with government and industry across a range of contexts. In this Conclusion chapter, we revisit the foundations of The Method, reflect on its current form and application, and ask the question, "Did we achieve our goals?", which we committed to in the Introduction chapter twelve months ago. We also ask readers of the BehaviourWorks Australia Method Book to share their stories in how they have used the chapters and tools, before making one final commitment in relation to our future plans for the book.

Submitted in total fulfilment of the requirements for the degree of Doctor of Philosophy to the Centre for Alcohol Policy Research, School of Psychology and Public Health, College of Science, Health, and Engineering, La Trobe University, Victoria, Australia.

Decision-making is the act of choosing between two or more courses of action. In context of problem solving, decision-making involves choosing between possible solutions to a problem.

This thesis has been submitted in total fulfilment of the requirements for the Doctor of Philosophy to the School of Psychology and Public Health, La Trobe University, Victoria, Australia.

The purpose of this study is to discover the future leadership role in the presence of Artificial Intelligence and how these smart technologies will change, assist and transform the leadership decision-making within the Welsh manufacturing sector.

In recent years, there has been an increase in environmental awareness in the United States leading to steady growth in environmentally conscious consumerism. These changes have come in response to issues such as the energy crisis, climate change, exponential population growth, and rapid urbanization. This fact is further supported by environmental campaigns and the green movement. Looking to the future of green home marketing, understanding the green consumer behavior of Generation Z (GenZ) is important for environmental and business reasons. The purpose of this research is to better understand the perception of GenZ on Green Homes (GHs). The study uses the lenses of dual inheritance and normative motivation theory to explain the influence of benefits and norms related to environmentalism and sustainability on GenZ consumers’ green behavior. This study seeks to evaluate 1) GenZ’s preferences related to Green Home Features (GHFs), 3) the extent of the influence of certain barriers on the adoption of GHFs, and 3) the types of motivation (intrinsic, instrumental and non-normative) influencing GenZ towards green home consumerism. Data was collected using an online survey questionnaire exclusively at Purdue University during March – April of 2021 (IRB 2020-1414). One hundred sixteen GenZ participants responded to the survey.The findings show that these GenZ consumers prefer a certain type of GHFs over others. Additionally, based on descriptive tests of GHFs, energy-related features were the most prized features, while the least preferred was water-efficient features. Descriptive tests on barriers suggest that GenZ consumers perceive the lack of choice in selecting GHFs in their homes to be a top barrier, followed by a lack of information and the perceived effort to analyze GHFs. Inferential tests for the same indicated that GenZ consumers perceive these barriers differently. Lastly, for GenZ consumers, intrinsic and non-normative motivations significantly affect their willingness to buy GHs. The findings concur with previous studies on green consumer behavior, yet they provide a new benchmark for understanding GenZ consumer behavior on GHs and an updated view of what GHFs they prefer. This research can be used by home marketers and policy makers to study future home trends, attract more potential homeowners to GHs, and help create a sustainable environment for future generations.

Decision-makers in the healthcare market, be they a healthcare consumer, provider, insurer or regulator, constantly interact and exchange information with each other. However, one party often holds a greater knowledge than the other. Hospitals expect that physicians will choose the most efficient treatment, whereas patients have to rely on medical decisions made by their physician. To equalise the information in the healthcare industry has long been seen as a way to improve market efficiency and performance. The aim of this collection of empirical studies is to study the decision-making behaviour of each agent and its consequences in the healthcare market.

This 'investigative report' dissertation examines the strength of the link between the housing problems and foreign investment, specifically the two interrelated aspects of this subject matter, i.e. ���unoccupied residential units��� and ���foreign investment in real estate��� in Vancouver, British Columbia.

Fake News comes in many, pervasive forms, and has dominated the conversation aroundimportant world events, including the 2016 and 2020 United States presidential election. In thisstudy, we explore how photos as a medium may be impacting how people are able to distinguishreal from fake news. Previous research has explored how elements such as news sources, traitsand characterizations of people, and system 1 and 2 processing affect how people discern fakefrom real news. However, the question of how different types of media may be impacting howpeople read news has yet to be explored. In the current study participants judged the veracity of30 news article headlines, all of which actually circulated in the US around 2016 to more currenttimes. Inclusion of a photo did not significantly change how well participants discriminated fakefrom real news, suggesting that people do not use photos as a cue for the believability of a story.Further research is necessary to better understand how photos and other forms of media mayimpact the believability of news.

No Fault Founds (NFFs) are an expensive problem faced by the airline industry. The underlying cause of NFFs are a major focus of research work in the field, but the dearth of consistent data is a roadblock faced by many decision makers. An important risk factor identified is the occurrence rate of NFFs.This research work aims to help decision makers in the Airline Maintenance, Repair and Overhaul teams, when faced with recurring NFFs, to make a choice based on value derived from the system and risk preference of the decision maker under uncertainty. The value of the aircraft fleet is laid out using Net Present Value at every decision point along the system life cycle while accounting for the uncertainty in the failure rate information. Two extreme decisions are considered for the decision maker to choose between: rebooting the system every time a failure occurs and results in an NFF which allows for it to recur while reducing uncertainty of the failure rate; or eliminating the failure mode which assumes that the failure does not recur and therefore completely removes the uncertainty. Both decisions have their associated uncertain costs that affect the NPV calculated. We use a Monte Carlo approach to estimate the expected profit from deciding to eliminate the failure mode. We make use of Expected Utility Theory to account for the risk preference of a decision maker under uncertainty and build an Expected Utility Maximizing decision framework.To conclude we give some guidance to interpret the results and understand what factors influence the optimal decision. We conclude that not accounting for uncertainty in estimating a failure rate for the future along with uncertainty in NFF costs can lead to an undesirable decision. If the decision maker waits too long to gather more information and reduce uncertainty, then rebooting the system for the remaining life could be more worthwhile than spending the large amount of money to Eliminate a failure mode. Finally, we conclude that, despite uncertainties in information of occurrence rates and costs of NFFs, an Expected Utility maximizing decision between the two options considered – Reboot and Eliminate – is possible given the available information.

Background: The challenging and stochastic nature of military operations require combatants to operate at a high level whilst coping with numerous physical (e.g. load carriage) and cognitive challenges (e.g. decision making). Purpose: To investigate the effect of military specific physical activity (MSPA) on relevant parameters of physical and cognitive performance.Research Design: 1) Developing a representative MSPA protocol and physical and cognitive performance measures. 2) Quantifying the physical demands of the MSPA protocol. 3) Establishing the reliability and validity of the cognitive performance measures. 4) Quantifying the MSPA protocol’s effect on the physical and cognitive performance. Research Progress: A combined load carriage and fire and manoeuvre task was selected as the representative MSPA based on criticality and frequency of completion during military operations. Three physical performance measures well correlated military performance were selected 1) medicine ball throw, 2) weighted counter-movement jump 3) maximal isometric voluntary contraction. To assess cognitive performance a shoot/don’t shoot task and auditory n-back task were chosen based on the importance of working memory during military operations.Military Relevance: The proposed research design should increase the understanding of physical and cognitive function pre-, during-, and post-MSPA and for the development and assessment of mitigation strategies.

Bushfire Risk in Late-modernity: An Examination of Risk Perspectives and Ontological Security Structures in Victorian Urban-rural Interface Residents

Business rules influence the behaviour of business processes and subsequent outcomes such as profitability and customer service. This is particularly important in the services sector where customers, and their needs, are different. This thesis addresses the problem of creating a set of business rules that will give the best business outcomes for the types of customer that we expect to service. In addition, the potential for business rules to work alongside and support, instead of simply replace, the human decision maker is explicitly considered. The theory is developed and then applied to a case study in loan approval. The results indicate that there is merit in this approach and that optimised business rules can improve business outcomes.

The BehaviourWorks Australia Method Book provides practitioners with a prioritised list of research and decision-making tools that will increase the chances that any behaviour change efforts will be effective. The Book is based on our extensive experience of applying different behaviour change skills and approaches in partnership with government and industry across a range of contexts. In this Introductory chapter, we outline some of the key benefits of applying the behavioural sciences to influence outcomes related to economic prosperity, better health, social inclusion and environmental sustainability (including specific reference to Covid-19), followed by an overview of the Method. We then describe our plans to release a chapter each month throughout 2021 that focuses on a specific skill or approach (along with a host of complementary resources, including future training and collaboration opportunities). Finally, we describe how we will be applying the behavioural sciences to our author team to deliver the book as planned.

Traditionally, games have been viewed as a form of entertainment. Yet, given how engaging games can be their effects can be beneficial in many domains. This paper explores the use of games as a methodology of exploring the decision-making processes demonstrated by a group of information security specialists when role-playing as malicious actors.To achieve this a board game has been designed which enables players to impersonate different types of attackers each with different motivations and goals. Each player is given a set of tools, techniques and procedures (TTPs) in form of cards and a set of end goals which need to be achieved in order to ‘win’ the game. By interacting with the facilitator, who is also representing the defending organisation or location, they voice out their intended actions and decisions and play a TTP card of their choice. By adopting a persona in an engaging fictional setting players are freed from concerns associated with self-image maintenance and concerns about reputational damage and ultimately, are better able to construct creative and malicious attacks. The game methodology also provides a less limited framework for the data gathering, and with suitable facilitation allows the capture of a very diverse set of attacks.By using this methodology, it is possible to gather a more diverse set of both decision-making behaviour and attacks, improving our understanding of offensive actors. This understanding will then be used to influence the creation of an agent-based simulation of these actors and scenarios.

We investigated the time loss bias: overestimation of time lost after a speed decrease from high speeds and underestimations after decrease from low driving speeds. The bias depends to a great extent on the human inability to use correctly inverse variables in intuitive judgments. Participants judged the speed decrease from one speed (e.g., 130 kmph) that would give the same time loss as a decrease from another speed (e.g., from 40 to 30 kmph). We carried out descriptive spectral analyses of distributions of judgments for each problem. Each distribution peak was associated with a judgment rule. The first study found two different judgment processes both leading to the time loss bias: a Difference process rule used for 20% and a Ratio rule used for 31% of the judgments. The correct rule applied to 10% of the judgments. The second study replicated the first study and added verbal protocols. The results showed that the Ratio rule was most common (41%) followed by the Difference (12%) and correct (8%) rules. Verbal reports supported these results.The data can be reached and processed by open statistical programs like JAMOVI https://www.jamovi.org/ ,or any Rbased statistical program as well as by PSPP https://www.gnu.org/software/pspp/

Critical incidents are environments that can be characterised by complexity, high-stakes, ambiguity, time-urgency and uncertainty, and often involve a multi-agency response (e.g. Fire and Rescue, Police, and the Military); for example, in terror attacks (e.g. Manchester bombings, London Bridge), fire disasters (e.g. California wildfires, Grenfell Towers), and the 2020 COVID-19 pandemic. In this respect, critical incidents are distinctive, dynamic events in which multi-agency systems lack the situational awareness and operational experience to make effective strategic and tactical decisions. Whilst research has begun to understand and explore decision-making in complex environments, there is limited research that focuses on understanding the processes used to coordinate effective responses in situ within critical incident environments; specifically, critical incident decision-making. This review sought to (i) identify relevant studies, (ii) critically appraise concepts that relate to the central theme of critical incident decision-making in-situ, and (iii) examine the barriers that compound effective strategic and tactical decision-making. The research identified numerous factors that affect the decision-making process (e.g. political agendas, disparity between operational objectives, and intra-and-inter agency collaboration). Additionally, several theoretical and applied decision-making frameworks were identified (e.g. Joint Decision Model; JESIP), that to date, have not factored in how complex, high-stake multi-agency decisions are made under conditions of uncertainty and time-urgency. This presentation will discuss the theoretical implications across security, defence, and law enforcement contexts and present pathways for future research.

Engineering designers commonly make sequential information acquisition decisions such as selecting designs for performance evaluation, selecting information sources, deciding whom to communicate with in design teams, and deciding when to stop design exploration. There is significant literature on normative decision making for engineering design, however, there is a lack of descriptive modeling of how designers actually make information acquisition decisions. Such descriptive modeling is important for accurately modeling design decisions, identifying sources of inefficiencies, and improving the design process. To that end, the research objective of the dissertation is to understand how designers make sequential information acquisition decisions and identify models that provide the best description of a designer’s decisions strategies. For gaining this understanding, the research approach consists of a synthesis of descriptive theories from psychological and cognitive sciences, along with empirical evidence from behavioral experiments under different design situations. Statistical Bayesian inference is used to determine how well alternate descriptive decision models describe the experimental data. This approach quantifies a designer's decision strategies through posterior parameter estimation and Bayesian model comparison. Two research studies, presented in this dissertation, focus on assessing the effects of monetary incentives, fixed budget, type of design space exploration, and the availability of system-wide information on information acquisition decisions. The first study presented in this dissertation investigates information acquisition by an individual designer when multiple information sources are available and the total budget is limited. The results suggest that the student subjects' decisions are better represented by the heuristic-based models than the expected utility(EU)-based models. While the EU-based models result in better net payoff, the heuristic models used by the subjects generate better design performance. The results also indicate the potential for nudging designers' decisions towards maximizing the net payoff by setting the fixed budget at low values and providing monetary incentives proportional to the saved budget.The second study investigates information acquisition through communication. The focus is on designers’ decisions about whom to communicate with, and how much to communicate when there is interdependence between subsystems being designed. This study analyzes team communication of NASA engineers at a mission design laboratory (MDL) as well as of engineering students designing a simplified automotive engine in an undergraduate classroom environment. The results indicate that the rate of interactions increases in response to the reduce in system-level design performance in both settings. Additionally, the following factors seem to positively influence communication decisions: the pairwise design interdependence, node-wise popularity (significant with NASA MDL engineers due to large team size), and pairwise reciprocity.The dissertation work increases the knowledge about engineering design decision making in following aspects. First, individuals make information acquisition decisions using simple heuristics based on in-situ information such as available budget amount and present system performance.The proposed multi-discipline approach proves helpful for describing heuristics analytically and inferring context-specific decision strategies using statistical Bayesian inference. This work has potential application in developing decision support tools for engineering design. Second, the comparison of communication patterns between student design teams and NASA MDL teams reveals that the engine experiment preserves some but not all of the communication patterns of interest. We find that the representativeness depends not on matching subjects, tasks, and context separately, but rather on the behavior that results from the interactions of these three dimensions. This work provides lessons for designing representative experiments in the future.

Many new anticoagulant interventions have emerged for stroke prevention in atrial fibrillation such as novel oral anticoagulants (NOACs) and warfarin care bundles. To date, the overall efficacy and cost-effectiveness of warfarin care bundles in comparison with NOACs is still unknown, especially in the healthcare context of low- and middle-income countries. Therefore, this thesis aimed to explore the clinical and economic outcomes of these interventions in patients with atrial fibrillation, in such healthcare setting. This thesis demonstrated the value of clinical evidence obtained systematically and how economic evaluation may facilitate healthcare decision-making on the choices of anticoagulants, based on scarce resources allocation.

This thesis investigates the dynamic interactive process of how individual motivation leads to the desired organizational outcome. By understanding individual differences in personality, it is possible to elicit the maximum trust and cooperation potential of every employee. The results demonstrate that the quantum of extrinsic rewards needs to be large enough to improve employee trust and cooperation meaningfully. Hence, employers could gain insights into the behavioral outcomes in the workplace and make strategic organizational decisions through excessive extrinsic rewards to augment employee trust and cooperation.

The primary research question of this dissertation is, \textit{How do contestants make sequential design decisions under the influence of competition?} To address this question, I study the influence of three factors, that can be controlled by the contest organizers, on the contestants' sequential information acquisition and decision-making behaviors. These factors are (i) a contestant's domain knowledge, (ii) framing of a design problem, and (iii) information about historical contests. The \textit{central hypothesis} is that by conducting controlled behavioral experiments we can acquire data of contestant behaviors that can be used to calibrate computational models of contestants' sequential decision-making behaviors, thereby, enabling predictions about the design outcomes. The behavioral results suggest that (i) contestants better understand problem constraints and generate more feasible design solutions when a design problem is framed in a domain-specific context as compared to a domain-independent context, (ii) contestants' efforts to acquire information about a design artifact to make design improvements are significantly affected by the information provided to them about their opponent who is competing to achieve the same objectives, and (iii) contestants make information acquisition decisions such as when to stop acquiring information, based on various criteria such as the number of resources, the target objective value, and the observed amount of improvement in their design quality. Moreover, the threshold values of such criteria are influenced by the information the contestants have about their opponent. The results imply that (i) by understanding the influence of an individual's domain knowledge and framing of a problem we can provide decision-support tools to the contestants in engineering design contexts to better acquire problem-specific information (ii) we can enable contest designers to decide what information to share to improve the quality of the design outcomes of design contest, and (iii) from an educational standpoint, we can enable instructors to provide students with accurate assessments of their domain knowledge by understanding students' information acquisition and decision making behaviors in their design projects. The \textit{primary contribution} of this dissertation is the computational models of an individual's sequential decision-making process that incorporate the behavioral results discussed above in competitive design scenarios. Moreover, a framework to conduct factorial investigations of human decision making through a combination of theory and behavioral experimentation is illustrated.

The authors believe this free of charge book, Fundamentals of Infrastructure Management, will expand the impact of the material and help improve the practice of infrastructure management. By ‘free of charge,’ we mean that the material can be freely obtained, but readers should devote time and effort to mastering the material. We have provided problem assignments for various chapters, and we strongly urge readers to undertake the problems as a learning experience. This book grew out of a decade of co-teaching a course entitled ‘Infrastructure Management’ at Carnegie Mellon University. Our teaching philosophy was to prepare students for work in the field of infrastructure management. We believe that infrastructure management is a professional endeavor and an attractive professional career. The book is co-authored by two accomplished engineers - each representing professional practice, academic research and theoretical evaluation. Their collective strengths are presented throughout the text and serve to support both the practice of infrastructure management and a role for infrastructure management inquiry and search. Importantly, both co-authors have academic research interests (and a number of research publications) on various topics of infrastructure management. That said, the primary audience for this book is expected to be professionals intending to practice infrastructure management, and only secondarily individuals who intend to pursue a career of research in the area.The text draws examples and discusses a wide variety of infrastructure systems, including roadways, telecommunications, power generation, buildings and systems of infrastructure. We have found that some common fundamentals of asset management, analysis tools and informed decision-making are useful for a variety of such systems. Certainly, many infrastructure managers encounter a variety of infrastructure types during their professional careers. Moreover, due to the functional inter-dependencies of different infrastructure systems, it is certainly advantageous for managers of one infrastructure type to understand other types of infrastructure. For example, roadway managers rely upon the power grid for traffic signal operation.The first segment of this book presents fundamental concepts and processes (e.g., the FHWA Asset Management Process), followed by chapters on specific types of infrastructure. In the first segment of the book, we generally use roadways as an example infrastructure application but not exclusively. We have chosen roadways since they are ubiquitous and nearly everyone is familiar with their use (and deterioration!). We are convinced that a life cycle or long-term viewpoint is essential for good infrastructure management. There are always pressures to adopt short term thinking in making investment and management decisions. Political election cycles and short-term stock performance certainly focus attention on immediate priorities or issues. Nevertheless, many infrastructure investments will last for decades or more, and providing good performance over an entire lifetime is critical for good infrastructure management. Even virtual decisions such as the adoption of a particular performance standard for a facility component are likely to have long-term implications.Of course, infrastructure managers may face budget limits or other constraints that preclude long-term optimization. A result is the deferred maintenance and functional obsolescence that exist in many infrastructure systems. However, understanding the effects and implications of these constraints is an important task for infrastructure managers.As a fourth organizational concept, we believe that infrastructure management in a process with multiple objectives (as well as multiple constraints). In particular, infrastructure management should adopt a ‘triple bottom line’ to consider economic, environmental and social impacts. Again, infrastructure managers may be charged with focusing solely on costs of providing services, but infrastructure certainly has implications for the natural environment and for society. For example, infrastructure management typically involves a large number of workers and affects a large number of users, so social impacts are significant. Throughout this book, we will try to address the impacts of infrastructure decision making with regard to these multiple objectives.Students in our Infrastructure Management course were usually first year graduate students or senior undergraduate students. While most were majoring in engineering disciplines, we also had architects, computer scientists and public policy students successfully complete the course. Indeed, many of our students ended up pursuing a career in some form of infrastructure management, and we are particularly grateful to all our students for their insights, their questions and their feedback on the material.Our course in Infrastructure Management was a full semester with class sessions for 30 to 35 hours over the course of a semester. The order of coverage of material generally followed the order in this book, except that we usually covered one or two infrastructure chapters early in the course to provide context for examples. The course involved class sessions (with a mix of lecture, discussion, videos and in-class exercises), homework assignments and a semester-long group project of the student’s choosing. We considered the group project fundamental to a substantive understanding of the concepts expressed in the text. Our textbooks ranged from peer reviewed journal papers to the literal infrastructure “news of the day”, and our use of those materials is in part responsible for the framework of this text. We also invited a few practicing infrastructure managers to guest lecture on their own their own activities, problems and successes as practitioners in this sub-discipline. We always included a tour of campus infrastructure, visiting utility tunnels, rooftops, and mechanical rooms – spaces not generally open to students.The text features discussions and materials covering the following infrastructure management related topics: Introduction to Infrastructure Management, Importance of Infrastructure, Goals for Infrastructure Management, Role of Infrastructure Managers, Organizations for Infrastructure Management, Asset Management Process, Inventory, Inspection and Condition Assessment, Deterioration Modeling, Decision Making and Forecasting from Condition Assessment, Regression Models, Markov Deterioration Models, Artificial Neural Network Deterioration Models, Failure Rates and Survival Probabilities, Fault Tree Analysis, Optimization and Decision Making, Performance, Usage, Budget and Cost Functions, Short Run Cost Functions for Infrastructure, Life Cycle Costs, Long Run Investment Decisions and Cost Functions, Decision Analysis and Monte Carlo Simulation for Investment Decisions, Interdependence & Resiliency, Contract and Workflow Management, Commissioning New Facilities, Benchmarking and Best Practices.In addition, the text examines in some detail the following infrastructure systems: Roadway Infrastructure, Building Infrastructure, Water Infrastructure, Telecommunications Infrastructure, Electricity Power Generation Infrastructure, Base, Campus, Park and Port Infrastructure. This list is certainly not exhaustive, and in fact, the various strategies, techniques and tools expressed in the text can be readily extended to virtually any infrastructure system. The second edition is available at: https://doi.org/10.1184/R1/5334379.v1.The third edition is available at: https://doi.org/10.1184/R1/5334379.v2.

This .zip file contains all online appendices, Mplus program input and output, as well as other files relevant to the two-paper series From Data to Causes in Organizational Research Methods, which describe and contrast the General Cross-Lagged Panel Model (GCLM) with other approaches. The YouTube presentation covering the GCLM that goes along with the PowerPoint file for Paper I can be viewed here: https://youtu.be/tHnnaRNPbXs

While there is evidence about the relationship between career development and psychological outcomes, more work is needed to understand how career development is related to personal mental health outcomes in college students. Studying some of the social and cognitive predictors of self-efficacy, this study espouses a holistic perspective to career development and aims to better understand its impact on well-being. Using social cognitive career theory (SCCT) and Super's life-span, life-space theory, this study examines how social (e.g., parental support) and cognitive (e.g., career values awareness) factors influence career decision-making self-efficacy, and furthermore, how this impacts well-being in undergraduate students. Specific mediation hypotheses were assessed, including the mediating role of career values awareness in the relationship between parental support and career decision-making self-efficacy, and the mediating effect of career-decision-making self-efficacy on well-being. Data were collected from 1446 undergraduate students at a large Midwestern public land-grant university through an online survey. Using structural equation modeling to analyze the data, results indicated that: (a) career values awareness mediated the relationship between parental behaviors and CDMSE; (b) CDMSE mediated the relationship between parental behaviors and well-being; and (c) CDMSE mediated the relationship between career values awareness and well-being. In an alternative model, parental support and socioeconomic status (SES) were also found to be significant positive predictors of well-being. Post hoc analysis revealed that academic standing (i.e., year in school) did not moderate the relationship between CDMSE and well-being. Limitations of the study and recommendations for future research are suggested along with implications for clinical practice.

This research was undertaken to develop ways to support the decision-making of anaesthesia teams during challenging, time-pressured situations. The research focused on decisions relating to airway management: the critical support of a patient’s breathing functions while the patient is anaesthetised. A human-centred design approach was followed using qualitative research methods of field observations, interviews and focus groups. Initially, key decisions and how they were made in practice were identified. After understanding how and when decisions are made, decision support concepts were identified. The main intervention selected was an organised airway equipment tray for design and development.

Research Question: Despite the proven benefits of utilizing a doula, only 6% of United States women choose to have a doula present at birth. What explains this lack of doula utilization? Methods:This research employed the mental models approach, an in-depth interviewing and analysis method deriving from decision science, to examine the decision making process of expectant mothers with regard to the use of doulas. The process included 5 interviews with experts including OBGYNs, midwifes, and doulas,and 11 interviews with pregnant women.Analysis:A gap analysis compares the mental models of experts versus pregnant women.Results:Pregnant women have difficulty predicting what labor will be like, and thus how much continuous labor support they will need and want(a hot cold empathy gap). They also lack essential knowledge about what a doula is and does. They report not receiving information about doulas from their health care providers, which contributes to this gap in knowledge and is interpreted as a signal that the provider does not support the choice to use a doula. Lastly, pregnant women anticipate potentially negative relationship consequences when they imagine using a doula—both with their health care provider as well as with their partner. Conclusions/Implications: Health care providers can provide preliminary information about doulas to their patients via methods such as a poster or pamphlet. This would not only give pregnant women basic information on the benefits of doulas but also signal that they support the decision. Doula communications can better address women’s knowledge needs and relationship fears by including information about their role in supporting both women and partners in the child birth experience.

or consumers, managing privacy online requires navigating a complex process of interrelated choices. This process may be conceived of as "cascaded," in that a combination of upstream choices (e.g., of privacy settings on a social network site) and downstream choices (e.g., of what to reveal on the site) together determine ultimate privacy outcomes. In a series of experiments, we examine the potential impact of choice architecture in cascaded privacy choice settings. We investigate how changes in choice frames implemented by service providers can influence consumers' upstream disclosure settings, often in ways that they are unaware of and that may be destructive to them. Whether the effects of choice frames upstream are ultimately detrimental to individuals' privacy, however, depends on whether they are offset by more or less protective downstream choices. Thus, we also examine whether such upstream effects of choice architecture are "mitigated" through changes in downstream self-disclosure. We find, first, that various manipulations of decision frames, common in privacy contexts, significantly impact participants' upstream choice of disclosure settings. Second, we do not find evidence that the impact of choice architecture upstream is mitigated downstream: participants' self-disclosure rates do not adjust or change in response to choice architecture-induced changes in upstream choices. These findings call into question both policy makers' and industry advocates' reliance on choice-based privacy protection mechanisms, contribute to an emerging behavioral perspective on privacy decision making, and highlight the importance of accounting for the cascaded nature of privacy decision making in both policy and managerial settings.

Use of a left ventricular assist device (LVAD) can benefit patients with end stage heart failure, but only with careful patient selection. In this study, previously derived Bayesian network models for predicting LVAD patient mortality at 1, 3, and 12 months post-implant were evaluated on retrospective data from a single implant center. The models performed well at all three time points, with a receiver operating characteristic area under the curve (ROC AUC) of 78, 76, and 75%, respectively. This evaluation of model performance verifies the utility of these models in “real life” scenarios at an individual institution.

We quantitatively evaluate the role of knowledge when detecting cyber-attacks.Knowledge supports the identification of the relevant cues for classifying events.Knowledge facilitates integration of cues when detecting malicious network events.Knowledge makes a decision maker more aware of the type of cyber-attack (context).Situated knowledge is crucial to correctly integrate events and detect a cyber-attack. Ensuring cyber security is a complex task that relies on domain knowledge and requires cognitive abilities to determine possible threats from large amounts of network data. This study investigates how knowledge in network operations and information security influence the detection of intrusions in a simple network. We developed a simplified Intrusion Detection System (IDS), which allows us to examine how individuals with or without knowledge in cyber security detect malicious events and declare an attack based on a sequence of network events. Our results indicate that more knowledge in cyber security facilitated the correct detection of malicious events and decreased the false classification of benign events as malicious. However, knowledge had less contribution when judging whether a sequence of events representing a cyber-attack. While knowledge of cyber security helps in the detection of malicious events, situated knowledge regarding a specific network at hand is needed to make accurate detection decisions. Responses from participants that have knowledge in cyber security indicated that they were able to distinguish between different types of cyber-attacks, whereas novice participants were not sensitive to the attack types. We explain how these findings relate to cognitive processes and we discuss their implications for improving cyber security.