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Humans have difficulties grasping the notion of exponential growth and often underestimate the accumulated final value, a phenomenon called exponential growth bias (EGB). During the COVID-19 pandemic, this tendency led to the inaccurate judgment of the virus spread, ultimately making safety measures seem less important. In prospect theory, loss aversion refers to the tendency of perceiving loss as more severe than a gain of the same magnitude is perceived as good. The question addressed was whether loss aversion through the valence of framing influences the judgments of exponential changes within the context of COVID-19. Furthermore, the association between EGB and the individual characteristic Need for Cognition (NFC) was investigated. Participants (n=129) were randomized into one of the two framing conditions (Recovery or Infection) and were presented with six EGB problems with different change rates and the six-item version of the Need for Cognition Scale. The results confirmed the existence of EGB at all growth rates (+5%, +15%, +25%), while the effect of EGB was mixed for exponential decline. The framing did not show a considerable effect on the accuracy of judgments. Simple linear regression analyses indicated that NFC moderates the effect of EGB at higher growth rates (i.e., at +15% and +25%). Overall, the results were more consistent and clearer for exponential growth than for exponential decline. The underestimation of exponential growth in the context of COVID-19 is quite alarming as it entails the risk of insufficient behavioral changes, which can lead to serious consequences for both the individual and society.

To mitigate the technical challenges faced by the next-generation smart power grid, in this thesis, novel frameworks are developed for optimizing energy management and trading between power companies and grid consumers, who own renewable energy generators and storage units. The proposed frameworks explicitly account for the effect on demand-side energy management of various consumer-centric grid factors such as the stochastic renewable energy forecast, as well as the varying future valuation of stored energy. In addition, a novel approach is proposed to enhance the resilience of consumer-centric energy trading scenarios by analyzing how a power company can encourage its consumers to store energy, in order to supply the grid’s critical loads, in case of an emergency. The developed energy management mechanisms advance novel analytical tools from game theory, to capture the coupled actions and objectives of the grid actors and from the framework of prospect theory (PT), to capture the irrational behavior of consumers when faced with decision uncertainties. The studied PT and game-based solutions, obtained through analytical and algorithmic characterization, provide grid designers with key insights on the main drivers of each actor’s energy management decision. The ensuing results primarily characterize the difference in trading decisions between rational and irrational consumers, and its impact on energy management. The outcomes of this thesis will therefore allow power companies to design consumer-centric energy management programs that support the sustainable and resilient development of the smart grid by continuously matching supply and demand, and providing emergency energy reserves for critical infrastructure. / Master of Science

In accordance with the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010, the Securities and Exchange Commission is required to propose and adopt clawback rules. After a financial statement restatement, a clawback is utilized to recover incentive compensation that was previously paid out to a manager based on the misstatement. My study investigates financial reporting executives' (FREs) decision-making after the external auditors have proposed a restatement that will lead to a clawback. I performed a web-based experiment that was electronically distributed to sixty FRE participants (i.e., CFOs, controllers, and treasurers) and manipulated executive compensation structure (i.e., a higher percentage of total compensation based on incentives or a lower percentage of total compensation based on incentives) and auditor industry specialization (i.e., industry-specialist or non-industry specialist) in a clawback environment. I hypothesized that higher incentives or the presence of a non-specialist auditor would cause FREs to be less likely to agree with an auditor's proposed restatement, more likely to involve the external auditor's national office, and more likely to request termination of the external auditors. Further, I posited that the two factors would interact for each of the three dependent variables. As predicted, my results reveal that FREs are less likely to agree with the restatement due to loss aversion when a higher proportion of their pay is incentive-based; however, auditor specialization does act to mitigate the influence of loss aversion by increasing their likelihood to accept the restatement. Additionally, I find that FREs are highly likely to request the involvement of the national office and very unlikely to request termination of the auditors across all conditions. In consideration of the upcoming clawback rules, this is a timely study that makes important contributions. First, I find an unintended negative consequence of clawback regulation, as my results indicate that clawbacks may exacerbate aggressive financial reporting decisions by FREs during a restatement negotiation. Further, I find that specialist auditors can act as effective monitors of FREs' behaviors in a clawback environment. Last, my results provide evidence for firms regarding the influence of executive compensation structures on FREs' decision-making in a clawback setting. / Ph. D.

Cyber-physical systems (CPSs) are large-scale systems that seamlessly integrate physical and human elements via a cyber layer that enables connectivity, sensing, and data processing. Key examples of CPSs include smart power systems, smart transportation systems, and the Internet of Things (IoT). This wide-scale cyber-physical interconnection introduces various operational benefits and promises to transform cities, infrastructure, and networked systems into more efficient, interactive, and interconnected smart systems. However, this ubiquitous connectivity leaves CPSs vulnerable to menacing security threats as evidenced by the recent discovery of the Stuxnet worm and the Mirai malware, as well as the latest reported security breaches in a number of CPS application domains such as the power grid and the IoT. Addressing these culminating security challenges requires a holistic analysis of CPS security which necessitates: 1) Determining the effects of possible attacks on a CPS and the effectiveness of any implemented defense mechanism, 2) Analyzing the multi-agent interactions -- among humans and automated systems -- that occur within CPSs and which have direct effects on the security state of the system, and 3) Recognizing the role that humans and their decision making processes play in the security of CPSs. Based on these three tenets, the central goal of this dissertation is to enhance the security of CPSs with human actors by developing fool-proof defense strategies founded on novel theoretical frameworks which integrate the engineering principles of CPSs with the mathematical concepts of game theory and human behavioral models. Towards realizing this overarching goal, this dissertation presents a number of key contributions targeting two prominent CPS application domains: the smart electric grid and drone systems. In smart grids, first, a novel analytical framework is developed which generalizes the analysis of a wide set of security attacks targeting the state estimator of the power grid, including observability and data injection attacks. This framework provides a unified basis for solving a broad set of known smart grid security problems. Indeed, the developed tools allow a precise characterization of optimal observability and data injection attack strategies which can target the grid as well as the derivation of optimal defense strategies to thwart these attacks. For instance, the results show that the proposed framework provides an effective and tractable approach for the identification of the sparsest stealthy attacks as well as the minimum sets of measurements to defend for protecting the system. Second, a novel game-theoretic framework is developed to derive optimal defense strategies to thwart stealthy data injection attacks on the smart grid, launched by multiple adversaries, while accounting for the limited resources of the adversaries and the system operator. The analytical results show the existence of a diminishing effect of aggregated multiple attacks which can be leveraged to successfully secure the system; a novel result which leads to more efficiently and effectively protecting the system. Third, a novel analytical framework is developed to enhance the resilience of the smart grid against blackout-inducing cyber attacks by leveraging distributed storage capacity to meet the grid's critical load during emergency events. In this respect, the results demonstrate that the potential subjectivity of storage units' owners plays a key role in shaping their energy storage and trading strategies. As such, financial incentives must be carefully designed, while accounting for this subjectivity, in order to provide effective incentives for storage owners to commit the needed portions of their storage capacity for possible emergency events. Next, the security of time-critical drone-based CPSs is studied. In this regard, a stochastic network interdiction game is developed which addresses pertinent security problems in two prominent time-critical drone systems: drone delivery and anti-drone systems. Using the developed network interdiction framework, the optimal path selection policies for evading attacks and minimizing mission completion times, as well as the optimal interdiction strategies for effectively intercepting the paths of the drones, are analytically characterized. Using advanced notions from Nobel-prize winning prospect theory, the developed framework characterizes the direct impacts of humans' bounded rationality on their chosen strategies and the achieved mission completion times. For instance, the results show that this bounded rationality can lead to mission completion times that significantly surpass the desired target times. Such deviations from the desired target times can lead to detrimental consequences primarily in drone delivery systems used for the carriage of emergency medical products. Finally, a generic security model for CPSs with human actors is proposed to study the diffusion of threats across the cyber and physical realms. This proposed framework can capture several application domains and allows a precise characterization of optimal defense strategies to protect the critical physical components of the system from threats emanating from the cyber layer. The developed framework accounts for the presence of attackers that can have varying skill levels. The results show that considering such differing skills leads to defense strategies which can better protect the system. In a nutshell, this dissertation presents new theoretical foundations for the security of large-scale CPSs, that tightly integrate cyber, physical, and human elements, thus paving the way towards the wide-scale adoption of CPSs in tomorrow's smart cities and critical infrastructure. / Ph. D. / Enhancing the efficiency, sustainability, and resilience of cities, infrastructure, and industrial systems is contingent on their transformation into more interactive and interconnected smart systems. This has led to the emergence of what is known as cyber-physical systems (CPSs). CPSs are widescale distributed and interconnected systems integrating physical components and humans via a cyber layer that enables sensing, connectivity, and data processing. Some of the most prominent examples of CPSs include the smart electric grid, smart cities, intelligent transportation systems, and the Internet of Things. The seamless interconnectivity between the various elements of a CPS introduces a wealth of operational benefits. However, this wide-scale interconnectivity and ubiquitous integration of cyber technologies render CPSs vulnerable to a range of security threats as manifested by recently reported security breaches in a number of CPS application domains. Addressing these culminating security challenges requires the development and implementation of fool-proof defense strategies grounded in solid theoretical foundations. To this end, the central goal of this dissertation is to enhance the security of CPSs by advancing novel analytical frameworks which tightly integrate the cyber, physical, and human elements of a CPS. The developed frameworks and tools enable the derivation of holistic defense strategies by: a) Characterizing the security interdependence between the various elements of a CPS, b) Quantifying the consequences of possible attacks on a CPS and the effectiveness of any implemented defense mechanism, c) Modeling the multi-agent interactions in CPSs, involving humans and automated systems, which have a direct effect on the security state of the system, and d) Capturing the role that human perceptions and decision making processes play in the security of CPSs. The developed tools and performed analyses integrate the engineering principles of CPSs with the mathematical concepts of game theory and human behavioral models and introduce key contributions to a number of CPS application domains such as the smart electric grid and drone systems. The introduced results enable strengthening the security of CPSs, thereby paving the way for their wide-scale adoption in smart cities and critical infrastructure.

This thesis analyzes factors affecting adoption of integrated pest management (IPM) techniques by Kenyan vegetable farmers, including the role of their risk preferences. It also analyzes factors affecting their pesticide applications and expenditures. A survey was administered to 450 Kenyan vegetable growers to identify their pest management practices, and a behavioral experiment was run to elicit their risk preferences utilizing. Cumulative Prospect Theory. Loss aversion was found to be correlated with higher likelihood of IPM adoption while risk aversion was associated with higher pesticide application rates and expenditures. The influence of IPM adoption on pesticide use differed by IPM technique. / Master of Science / Integrated Pest Management (IPM) techniques can improve small holder farmers' livelihoods by lowering production costs and decreasing dependence on chemical pesticides. Even though some IPM techniques have been available to Kenyan vegetable farmers since the 1990's, IPM adoption remains relatively low while chemical pesticide use remains high. A farm-household survey and behavioral experiment were conducted to identify factors that influence farmer decisions to adopt IPM and to apply pesticides. Factors that influence IPM adoption were found to differ from those that influence pesticide decisions. Furthermore, IPM adoption by Kenyan farmers does not decrease use of chemical pesticides for all IPM techniques.

Master of Science / Department of Architecture / David R. Seamon / This thesis provides an overview of some key researchers and research topics in the field of environment-behavior studies (EBS), an interdisciplinary field that examines ways in which the natural and human-made environments contribute to human well-being. A key aim of environment-behavior studies is to better understand clients’ and users’ environmental needs, and to design the physical environment accordingly. Specifically, this thesis highlights two key research questions: (1) What are environment-behavior studies and why are they relevant to architecture and environmental design? and (2) How can environment-behavior studies be drawn upon practically to generate more effective architectural and environmental design? To provide answers to these two questions, the thesis first introduces five “pioneers” in environment-behavior studies— psychologist Roger Barker, anthropologist Edward Hall, psychologist Robert Sommer, urban designer Kevin Lynch, and architect Christopher Alexander—and reviews their major work. This discussion provides a general understanding as to what environment-behavior studies involve and how they have design significance. Next the thesis overviews three major theories developed in environment-behavior studies: (1) territoriality theory; (2) cognitive-mapping theory; and (3) prospect-refuge theory. Each of these theories is overviewed, and pragmatic examples are provided to indicate each theory’s value for architecture and environmental design.

In 1979 Daniel Kahneman and Amos Tversky created the prospect theory. It became an accepted and appropriate theory in explaining decision making under risk. The prospect theory has been one of the most cited articles in economics and Kahneman received the Nobel Prize in Economic Sciences as a result of the creation and development of the theory. Therefore the prospect theory is considered to be more suitable compared to the previously accepted theory, the expected utility theory. Following the prospect theory, researchers have utilized it to describe individual but also corporate management decision making when faced with risk. In this thesis the authors will focus on the latter. Despite the prospect theory being a well-accepted theory, there have been several critics due to its limitations and Audia and Greve (2006) are one of these critics. Their study suggested that corporations under threat, i.e. small firms with low returns, act risk averse. The findings of Audia and Greve (2006) violate the prospect theory when considering small firms that have below target returns. They tested the theory on an industry that has the characteristics of having relatively high proportions of tangible assets. Audia and Greve (2006) also proposed that a similar conclusion could be drawn if tested on an industry characterized by having a high level of intangible assets. This thesis examines the applicability of the prospect theory in the Swedish automotive industry and staffing and recruitment industry. The characteristics of the two industries are that the automotive industry has a high proportion of tangible assets and the staffing and recruitment industry has a high level of intangibles. The authors test if the prospect theory can be used to describe the decision making of both industries but also test the theory on small and large firms. Following the results of this paper we show that the prospect theory can be applied to the Swedish automotive industry and staffing and recruitment industry, characterized by having high levels of tangible assets and intangible assets respectively. The theory can also be used to explain decision making under risk for small firms within both industries and large firms within the automotive industry. Even though the prospect theory was originally tested on individuals, the conclusion can be drawn that the prospect theory once again prevails as an explanation of the decision making in the management of corporations. It can describe the decision making of firms in the two industries having characteristics of different asset tangibility and for firms of different size.

本文討論退休金長期預期報酬率之設定。根據會計公報規定，公司之退休金長期預期報酬率必須符合其資產配置。但是在本文中我們發現資產配置並無法有效的反應公司的退休金長期預期報酬率，因此我們提出展望理論及盈餘管理兩種理論來解釋退休金長期預期報酬率之設定。我們發現經理人企圖透過改變退休金長期預期報酬率的假設來進行盈餘管理，同時退休金長期預期報酬率也會因為公司的風險態度而有所改變。 / Abstract: We try to find out the considerations for managers to set their assumptions of expected long term rate of return on pension plan assets (ROPA). First, we use the asset allocations of pension funds and historical returns to calculate the expected rate of return based on historical asset returns (EROPA). There is difference between ROPA are EROPA, suggests that asset allocations are not the only consideration when managers setting their ROPA assumption. Two theories are examined in this paper to explain such difference between ROPA and EROPA: earnings management and prospect theory. We use two models to test the earnings management, single accrual model and threshold model. We find that the intentions to smooth the reported income are the main incentives for managers to manipulation their ROPA. The incentive to do earnings management can partly explain the difference between ROPA and EROPA. However, in threshold model, we can not observe any evidence in our research. We also introduce prospect theory to examine the risk attitude. We find that managers’ risk attitude affect the setting of assumptions, too. We conclude prospect theory provides a good explanation of the difference between ROPA and EROPA.