Much contemporary political discourse in the US and industrialized west is defective. According to a number of scholars, such as Scott Aikin and Robert Talisse, this defectiveness can plausibly be explicated in terms of a breakdown in political civility. In this thesis, I scrutinize possible explanations for why incivilities are widespread in political discourse. My goal is to defend an explanation according to which citizen incivility in political discourse is blameless. To do this, I appeal to a principle of reciprocity. According to the principle of reciprocity, citizens are not required to maintain civility in political discourse if they have reason to believe that their interlocutors will not reciprocate civility. When applied to contemporary politics, this principle implies that ordinary citizens in democratic societies across the US and industrialised west are often justified in being uncivil in political debate. For these citizens often have no reason to believe that their interlocutors will be civil. If the reciprocity principle is right, then policies aimed at restoring civility in political discourse must be concerned to build citizen trust that others will reciprocate civility. Without this trust, citizens may not see themselves as having reason to be civil. The thesis is divided into two chapters. In chapter 1, I defend the justificatory account of incivility against two competing accounts of political incivility—identity and group theories. These accounts pathologize political incivility as a kind of irrationality, but based on the argument from reciprocity, I argue that political incivilities are often rational and so justified. In chapter 2, I analyse the kind of trust that is necessary to build more civility in political discourse. In particular, I develop and defend a conception of deliberative trust, which is defined as the belief that one’s interlocutor will reciprocally adhere to the norms of civility. / Thesis / Master of Arts (MA) / In this thesis, I scrutinize possible explanations for why incivilities are widespread in contemporary political discourse. By appeal to a principle of reciprocity, my ultimate goal is to defend an explanation according to which citizen incivility in political discourse is blameless. According to the principle of reciprocity, citizens are not required to maintain civility if they have reason to believe that their interlocutors will not reciprocate civility in political discussion. Based on this principle, I argue that ordinary citizens in democratic societies across the US and industrialised west are often justified in being uncivil in political debate. For these citizens often have no reason to believe that their interlocutors will be civil. If the justificatory account of incivility is on the right track, then policies aimed at restoring civility in political discourse must be concerned to build citizen trust that others will reciprocate civility. Without this trust, citizens may not see themselves as having reason to be civil in political debate.

Purpose: The relationship between context and e-governance has been gaining a significant momentum in academic circles due its social and technical complexities. There are many challenges posed by the disparity between the context and the system when it comes to e-governance in developing countries. This research aims to reveal more successful adoption of e-governance initiatives and exposes factors that hinder its implementation. We develop a conceptual framework showing the reciprocity between the context and the system or what is termed “Context-System Gap”. Therefore, this research will study the appropriateness of the context and its influence on the system and the influence of the system on the context. The purpose of this research is to explore the factors that enable successful e-government adoption in Lebanon, where e-governance is still at its initial stage. Most empirical research and theories on the implementation of e-governance in developing countries remain at the macro-level and miss out on the complexities of the context of deployment and the role of the gap between the citizens and the government. The purpose of this thesis is to provide an empirical model differentiating between the electronic context and the electronic system and shed a light over a new gap, government-citizen gap, in the adoption of e-government. Design/methodology/approach: Following previous research on e-government services adoption, this study uses several technology use and acceptance models and literature to examine the elements behind the adoption and use of e-government services in Lebanon from citizen and government perspectives. The research strategy is a quantitative method approach employing questionnaire. Quantitative data will be collected from e-government users (citizens) and statistical tests will be conducted in order to examine the relation between variables. Practical implications: The findings are useful for policy-makers and decision-makers to develop a better understanding of citizens' needs. The proposed model can be used as a guideline for the implementation of e-government services in developing countries. Originality/value: This study is the only one to examine the dimensions influencing citizens’ adoption of e-government technologies in developing countries using a unified model merging context and system elements.

In this dissertation study examines trust as an economic category, analyzes the notion of the firm as the unit of entrepreneurial activity. Examines the relationship between trust and risk, contract and quality business practices. Analyze the criteria and methods of evaluation of trust as factor of increase of efficiency of entrepreneurial activity, comparative analysis of business cultures of Russia and the USA. Empirical analysis has shown that trust is an important factor in enhancing performance of entrepreneurial firms; closely connected with such concepts as honesty, confidence, a positive reputation; associated with the concept of "time". The study revealed the factors contributing to the strengthening and the destruction of confidence in the business environment; proposed and applied the model to assess the level of confidence in the subject area; developed methodical recommendations on the formation of a trust company; the composed model of building trust in business, allowing companies to improve the efficiency and sustainability of their activities. / В диссертационном исследовании рассматриваются доверие как экономическая категория, анализируется понятие фирмы как единицы предпринимательской деятельности. Рассматривается взаимосвязь доверия и риска, контракта и качества ведения бизнеса. Анализируются критерии и методы оценки доверия как фактора повышения эффективности предпринимательской деятельности, проводится сравнительный анализ предпринимательских культур России и США. Эмпирический анализ показал, что доверие является важным фактором, повышающим эффективность деятельности предпринимательских фирм; тесно переплетается с такими понятиями как честность, уверенность, позитивная репутация; сопряжено с понятием «времени». В исследовании выявлены факторы, способствующие укреплению и разрушению доверия в предпринимательской среде; предложена и применена модель оценки уровня доверия к предметной области; разработаны методические рекомендации по формированию доверительной репутации фирмы; составлена модель построения доверия в предпринимательстве, позволяющая фирмам повысить эффективность и устойчивость их деятельности.

When measuring people’s trust, research show a negative trend where people’s trust over time is declining globally, where digitalization is accelerating the process. Trust is a key component in a democratic society and social studies has the task of communicating democratic values and integrate the students in the democratic process. The aim of the present study was therefore to examine how different aspects of the concept “Trust” are highlighted and portrayed within different fields of knowledge in textbooks for social studies in upper secondary school. Three aspects of trust was analyzed; social capital and trust in one’s surroundings; trust in the political system and its institutions; how the economic system influence people’s trust. The concept of trust was examined through a thematic analysis, with discourse analytical elements that calculated frequencies of latent and semantic value words. The analysis indicate that both textbooks contain a frequent space for discourses of trust, where social trust is highlighted. Furthermore the results showed a big difference between latent reasoning about trust and direct semantic reasoning about trust. When examining study questions and tasks similar results were found, where Arena 123 had the most latent codes in the answer options, while Perspektiv på samhället had the most direct trust frequencies.

In this thesis, we use methods from econometrics to empirically measure and quantify how digital information influences industries and markets. Specifically, we focus on two important areas of marketing: online reputation management, and competition between online and offline markets. In the first part of the thesis, we study the impact of management review responses, a popular reputation management mechanism, on consumer ratings. To do so, we exploit a difference in managerial practice across two hotel review plat- forms, TripAdvisor and Expedia: while hotels regularly respond to their TripAdvisor reviews, they never do so on Expedia. Based on this observation we employ a “difference-in-differences” design to identify the causal impact of management responses on ratings, and show that responding hotels see an average increase of 0.1 stars. We then turn to analyze the mechanisms behind this increase in ratings and show that by responding to reviews, hotels attract consumers who are inherently more positive, and therefore more likely to leave good reviews. In the second part of the thesis, we study peer-to-peer markets and their impact on traditional industries. We do so by looking at Airbnb, a sharing economy pioneer offering short-term accommodation. We combine data from Airbnb and the Texas hotel industry, and estimate the impact of Airbnb’s entry into the Texas market on hotel room revenue. To identify Airbnb’s causal impact on hotel room revenue, we use a “difference-in-differences” empirical strategy that exploits the significant spatiotemporal variation in the patterns of Airbnb adoption across city-level markets. We estimate that in Austin, where Airbnb supply is highest, the impact on hotel revenue is roughly 8-10% for the most affected hotels. Further, we find that affected hotels have responded by reducing prices, an impact that benefits all consumers, not just participants in the sharing economy. The results presented in this thesis have practical implications for firms seeking to improve their operations and marketing strategies, platforms seeking to design better and efficient marketplaces, and consumers who are often not aware of important dynamics that can be helpful in their decision-making process.

In the context of automated vehicles, transparency of in-vehicle intelligent agents (IVIAs) is an important contributor to drivers' perception, situation awareness (SA), and driving performance. However, the effects of agent transparency on driver performance when the agent is unreliable have not been fully examined yet. The experiments in this Thesis focused on different aspects of IVIA's transparency, such as interaction modes and information levels, and explored their impact on drivers considering different system reliability. In Experiment 1, a 2 x 2 mixed factorial design was used in this study, with transparency (Push: proactive vs. Pull: on-demand) as a within-subjects variable and reliability (high vs. low) as a between-subjects variable. In a driving simulator, twenty-seven young drivers drove with two types of in-vehicle agents during Level 3 automated driving. Results suggested that participants generally preferred the Push-type agent, as it conveyed a sense of intelligence and competence. The high-reliability agent was associated with higher situation awareness and less workload, compared to the low-reliability agent. Although Experiment 1 explored the effects of transparency by changing the interaction mode and the accuracy of the information, a theoretical framework was not well outlined regarding how much information should be conveyed and how unreliable information influenced drivers. Thus, Experiment 2 further studied the transparency regrading information level, and the impact of reliability on its effect. A 3 x 2 mixed factorial design was used in this study, with transparency (T1, T2, T3) as a between-subject variable and reliability (high vs. low) as a within-subjects variable. Fifty-three participants were recruited. Results suggested that transparency influenced drivers' takeover time, lane keeping, and jerk. The high-reliability agent was associated with the higher perception of system accuracy and response speed, and longer takeover time than the low-reliability agent. Participants in T2 transparency showed higher cognitive trust, lower workload, and higher situation awareness only when system reliability was high. The results of this study may have significant effects on the ongoing creation and advancement of intelligent agent design in automated vehicles. / Master of Science / This thesis explores the effects of system's transparency and reliability of the in-vehicle intelligent agents (IVIAs) on drivers' performance and perception in the context of automated vehicles. Transparency is defined as the amount of information and the way to be shared with the operator about the function of the system. Reliability refers to the accuracy of the agent's statements. The experiments focused on different aspects of IVIA's transparency, such as interaction modes (proactive vs. on-demand) and information composition (small vs. medium vs. large), and how they impact drivers considering different system reliability. In the experiment, participants were required to drive in the driving simulator and follow the voice command from the IVIAs. A theoretical model called Situation Awareness-based Agent Transparency Model was adopted to build the agent's interactive scripts. In Experiment 1, 27 young drivers drove with two types of in-vehicle agents during Level 3 automated driving. Results suggested that participants generally preferred the agent that provided information proactively, and it conveyed a sense of intelligence and competence. Also, when the system's reliability is high, participants were found to have higher situation awareness of the environment and spent less effort on the driving tasks, compared to when the system's reliability is low. Our result also showed that these two factors can jointly influence participants' driving performance when they need to take over control from the automated system. Experiment 2 further studied the transparency regarding the information composition of the agent's voice prompt and the impact of reliability on its effect. A total of 53 participants were recruited, and the results suggested that transparency influenced drivers' takeover time, lane keeping, and jerk. The high-reliability agent was associated with a higher perception of system accuracy and response speed and a longer time to take over when requested than the low-reliability agent. Participants in the medium transparency condition showed higher cognitive trust toward the system, perceived lower workload when driving, and higher situation awareness only when system reliability was high. Overall, this research highlights the importance of transparency in IVIAs for improving drivers' performance, perception, and situation awareness. The results may have significant implications for the design and advancement of intelligent agents in automated vehicles.

With the dramatic growth of vehicles around the world, Vehicular Ad-hoc Networks (VANETs) have been proposed as a solution to advance road safety, improve transportation efficiency, and satisfy road users. In the VANET environment, vehicles communicate with each other and with road infrastructure in an ad-hoc manner. This communication may be safety-related or non-safety-related and may often include vehicle information (e.g., location, direction, speed, and control), road conditions, and events. A key component in assessing the veracity of the information is the trustworthiness of the information source. Thus, trust evaluation is one of the main requirements of VANET design. In this work, we investigate performance improvements in the trust evaluation framework of VANETs. First, we propose a risk-based trust evaluation model (RTEAM) to estimate the risk of taking action or refraining from action regarding a reported event (in case of receiving conflicting messages about the event's existence). Some trust metrics such as direct trust, hop-based trust values, proximity to the event, and consequences of acting on a wrong decision are used to estimate the risk of the vehicle’s actions. Vehicles make individual decisions by seeking the action with the lowest risk. Second, we propose a fog-based reputation evaluation model (FREM) to support trust management framework. We promote fog computing as a new paradigm since it can provide several services to users in the edge layer. In our work, Fog supports the decision-making process in the reputation evaluation framework. Fog nodes play a key role in collecting vehicles' reputation records and cooperating with the roadside units (RSUs) to update these records. We propose the use of Digital Trustworthiness Cards (DTC), where the latest reputation evaluation of a vehicle automatically appears on its card. The benefits of the DTC are twofold: 1) the communication load on vehicles is reduced, and 2) historical trust records are established for each vehicle. We also take advantage of fog’s familiarity and greater knowledge of the vehicles that frequently visit its zones; with more intimate knowledge, fog can smartly employ vehicles to perform specific tasks based on their experiences. Further, we implement a strategy for establishing trust based on specific task categories. This permits a nuanced evaluation of the vehicle best suited for the task at hand and has the further benefit of preventing malicious vehicles from being naively trusted based on successful completion of unimportant or non-safety-related tasks. Finally, we expand the role of the fog in the decision-making process when vehicles need to ensure the existence of serious events. We propose a fog-based event validation model (FEVM) to validate the event’s existence through cooperation between vehicles and fog nodes. The vehicles are used as mobile fog nodes, which compute their confidence in events based on the available information. Fog nodes then validate the event after combining vehicles’ confidence values by applying the Extended Dempster-Shafer (EDS) theory of evidence. To test our proposed models, we conduct many experiments to investigate their performance and compare them with other existing models.

Vaccine prophylaxis can undoubtedly be classified among the most important medical discoveries of the last century. The World Health Organization estimates that each year vaccinations prevent between two and three million deaths. Despite vaccines’ safety and effectiveness, vaccine hesitancy, the delay or refusal of vaccines despite their availability, is a re-emerging issue in high income countries. In this thesis I examine this issue pre- and post-COVID-19 pandemic, investigating the main predictors of vaccine hesitancy and highlighting the cognitive processes involved in individual's decision-making. In the theoretical section, I rely on contributions from sociology, economics and public health studies to build a framework enlightening the most relevant predictors of vaccine acceptance, the perceived risk of infectious diseases and the trust in the vaccination process. Through recent development in cognitive sciences, I reframe the issue showing the importance of considering the way individuals perceive, process and retrieve information in developing an informed analysis of vaccine acceptance. In the first empirical chapter, I investigate whether it is possible to identify subgroups in the population characterized by different world-views based on different patterns of the relationship between perceived risk and trust measures. I further assess whether such partitioning hides different levels of vaccine acceptance and whether it also entails a mean of social stratification. In the second empirical chapter I further explore how certain cognitive processes, analytic and intuitive cognition, might be connected to a differential in vaccine acceptance. Furthermore, I highlight individuals’ qualitatively complex perceptions of risk, and I suggest how enhancing the attention on cognitive processes and affective concerns might be a key to addressing vaccine hesitancy. In the third empirical chapter, I investigate vaccine hesitancy during the COVID-19 pandemic. I exploit rich comparative longitudinal data and analyze the association between risk perceptions, trust, and willingness to be vaccinated at three different levels: between individuals, between countries and within countries over time. In this chapter, I underline the importance of disentangling the main relationships of this thesis at different levels of analysis, and stress that vaccine acceptance is a multifaceted topic that could involve issues far beyond its own boundaries.

Recent issues such as global economic crises, terrorism, and conservation efforts are making international collaboration a critical topic. While cultural diversity often brings with it new perspectives and innovative solutions, diversity in collaborative settings can also lead to misunderstandings and interaction problems. Therefore, there is a pressing need to understand the processes and influences of intercultural collaboration and how to manage the collaborative process to result in the most effective outcomes possible. In order to address this need, the current study examines the effect of ethnic diversity, perceived deep-level similarity, trust, and distrust on collaborative behavior and performance in decision-making dyads. Participants were assigned to either same-ethnicity or different-ethnicity dyads and worked together on a political simulation game in which they had to make complex decisions to solve societal problems and increase their popularity. The results of this study indicate that ethnically similar dyads reported higher levels of perceived deep-level similarity than ethnically dissimilar dyads, and that this perceived deep-level similarity served as the mediating mechanism between objective differences in ethnic diversity and trust and distrust, respectively. The findings also suggest that trust and distrust attitudes, when considered together as a multiple mediation model, mediate the positive relationship between perceived deep-level similarity and collaborative behavior. Finally, results show that collaborative behavior significantly predicts objective performance on the political decision-making simulation. The implications of this study for theory and practice are discussed along with the study limitations and several suggestions for future research.

Trust is explored in this thesis through the analysis of the robustness of wearable device based artificial intelligence based models to changes in data acquisition. Specifically changes in wearable device hardware and different recording sessions are explored. Three human activity recognition models are used as a vehicle to explore this: Model A which is trained using accelerometer signals recorded by a wearable sensor referred to as Astroskin, Model H which is trained using accelerometer signals from a wearable sensor referred to as the BioHarness and Model A Type 1 which was trained on Astroskin accelerometer signals that was recorded on the first session of the experimental protocol. On a test set recorded by Astroskin Model A had a 99.07% accuracy. However on a test set recorded by the BioHarness Model A had a 65.74% accuracy. On a test set recorded by BioHarness Model H had a 95.37% accuracy. However on a test set recorded by Astroskin Model H had a 29.63% accuracy. Model A Type 1 an average accuracy of 99.57% on data recorded by the same wearable sensor and same session. An average accuracy of 50.95% was obtained on a test set that was recorded by the same wearable sensor but by a different session. An average accuracy of 41.31% was obtained on data that was recorded by a different wearable sensor and same session. An average accuracy of 19.28% was obtained on data that was recorded by a different wearable sensor and different session. An out of domain discriminator for Model A Type 1 was also implemented. The out of domain discriminator was able to differentiate between the data that trained Model A Type 1 and other types (data recorded by a different wearable devices/different sessions) with an accuracy of 97.60%. / Thesis / Master of Applied Science (MASc) / The trustworthiness of artificial intelligence must be explored before society can fully reap its benefits. The element of trust that is explored in this thesis is the robustness of wearable device based artificial intelligence models to changes in data acquisition. The specific changes that are explored are changes in the wearable device used to record the input data as well as input data from different recording sessions. Using human activity recognition models as a vehicle, the results show that performance degradation occurs when the wearable device is changed and when data comes from a different recording session. An out of domain discriminator is developed to alert users when a potential performance degradation can occur.