Modeling individual preferences for energy sources: the case of IV generation nuclear energy in Italy

The planned re-introduction of nuclear energy in Italy was abandoned in the aftermath of the Fukushima nuclear accident. Twenty years earlier, soon after the Chernobyl accident, Italians had also voted against nuclear energy. However, a new nuclear energy technology, i.e. fourth generation, is under research and development. This paper investigates its social acceptance by means of a robust methodology, employing 1) choice experiments, 2) structural equation modeling and 3) information treatments within an online nation-wide survey. Results show a great deal of preference heterogeneity: the majority of the sampled respondents oppose new nuclear plants in Italy, with some not willing to accept any monetary compensation at all. However, another segment of respondents, more confident that fourth generation nuclear energy goals will be achieved, show a modest support towards the implementation of new nuclear projects. Additional variables were found to affect opposition

Public support for degrowth policies and sufficiency behaviours in the United States: a discrete choice experiment

Research on degrowth and its policy proposals has rapidly expanded, despite lacking empirical evidence on public perceptions. One conceptual proposition for affluent populations is that lifestyle changes, such as undertaking sufficiency-oriented behaviours, may engender degrowth policy support. Our research empirically investigated U.S. public support for degrowth policies, its relation to sufficiency behaviours, and whether a degrowth framing influenced policy support. In a pre-registered, online discrete choice experiment (N = 1012), we elicited perceptions of four commonly advocated degrowth policies - work time reductions, downscaling fossil fuel production, universal basic services, and advertising restrictions. Analyses revealed significant support for some specification of each alternative policy, especially fossil fuel caps and universal healthcare. We also found a significant positive association between sufficiency engagement and supporting fossil fuel restrictions. However, latent class analysis suggested that the link between behaviour and policy support was less consistent for socially oriented policies, and that those who supported such policies did not engage in sufficiency most frequently. Degrowth framing only significantly influenced preferences for universal healthcare. These findings suggest an appetite for advancing eco-social policies in the United States but point to a nuanced relationship between sufficiency lifestyles and degrowth policy support

Modeling individual preferences towards nuclear energy

This thesis investigates preferences for nuclear energy and the determinants of its social acceptance, through a combination of methods from Environmental Economics and Environmental Psychology. In particular, we use stated preference surveys to investigate the social costs of nuclear energy in three different contexts: 1) Italy, a country that currently has no nuclear power plants in operation, and twice expressed its disapproval through referenda; 2) United Kingdom (UK), a country with nuclear energy; and 3) the United Arab Emirates (UAE), a country that plans to introduce nuclear energy by 2020. The determinants of social acceptance of nuclear energy are assessed in each of these different contexts. We investigate preferences for current nuclear technology as well as preferences for a new advanced 4th generation nuclear energy technology. In addition, we analyse the effects of having a transient population on support for nuclear energy. Moreover, this thesis investigates a number of methodological issues pertaining to stated preference methods: 1) heuristics in choice modeling; 2) combination of choice modeling and structural equation modeling; and 3) links between propensity to contribute in contingent valuation questions and choices within the choice experiment tasks. Overall, the thesis aims to contribute to the debate on public acceptability of nuclear energy after the Fukushima accident. In addition, it provides a framework to model individual preferences towards energy sources and assess departures from fully compensatory decision processes

Individual preferences towards nuclear energy: the transient residency effect

Nuclear energy is an energy source that is usually unfavourable among the public due to its inherent risks. However, it presents a number of benefits, including the possibility to reduce emissions and the contribution to tackle climate change. Among the countries adopting nuclear energy, the United Arab Emirates (UAE) is unusual in that a large share of its residents consists of expatriates who live only part of their lives in the country with no (or highly unlikely) access to citizenship. This distinctive population structure offers the opportunity to investigate the effect of transient residency on acceptance and preferences towards nuclear energy. We conducted this investigation by designing a stated preferences-based survey, targeting an online nationwide sample. The survey collected information on socio-economic characteristics and attitudes, including views on perceived risks and benefits of nuclear energy, views towards different energy sources and life satisfaction. Results indicate that transient individuals, especially those who are more satisfied with their lives in the UAE, are significantly less likely to oppose the construction of new nuclear plants. These individuals are characterized by a more positive perception of benefits over risks arising from nuclear energy. Policy implications are discussed

Essays on choice modeling

The increased interest in modeling preference heterogeneity in Choice Experiments (CE) data has promoted the use of choice models within the family of Logit Mixture models. However, researchers have scarce guidance on how to select the appropriate model. A Monte Carlo study is set up to analyze the performance of different information criteria and tests used to discriminate between models, either nested or non-nested. In particular, within non-nested models, four criteria and three tests are assessed, all of them based on the Kullback-Leibler Information Criterion (KLIC): the AIC, AIC3, CAIC and BIC information criteria, and the tests for non-nested models proposed by Vuong, Horowitz and Ben-Akiva and Swait. Our results indicate that some criteria (especially CAIC) work better than others; and that, when feasible, information criteria should be complemented by the Vuong test, which has a low power, but it virtually never selects the wrong model, while both the Horowitz and the Ben-Akiva and Swait tests too often provide wrong indications. The paper concludes with a CE application dealing with public acceptance of wind farms, where the indications drawn from the Monte Carlo analysis are used to inform model selection

Essays on choice modeling

The increased interest in modeling preference heterogeneity in Choice Experiments (CE) data has promoted the use of choice models within the family of Logit Mixture models. However, researchers have scarce guidance on how to select the appropriate model. A Monte Carlo study is set up to analyze the performance of different information criteria and tests used to discriminate between models, either nested or non-nested. In particular, within non-nested models, four criteria and three tests are assessed, all of them based on the Kullback-Leibler Information Criterion (KLIC): the AIC, AIC3, CAIC and BIC information criteria, and the tests for non-nested models proposed by Vuong, Horowitz and Ben-Akiva and Swait. Our results indicate that some criteria (especially CAIC) work better than others; and that, when feasible, information criteria should be complemented by the Vuong test, which has a low power, but it virtually never selects the wrong model, while both the Horowitz and the Ben-Akiva and Swait tests too often provide wrong indications. The paper concludes with a CE application dealing with public acceptance of wind farms, where the indications drawn from the Monte Carlo analysis are used to inform model selection

Water-energy-nature nexus and religiosity in Kuwait

Over the past two decades, researchers and policymakers have become increasingly interested in considering the interactions between energy, water, and natural resource systems and sectors when designing climate change policy. This approach is known as ‘nexus thinking’. Its goal is to promote policy coherence by identifying optimal policy mixes that consider the impacts of policies across all sectors. This can help policymakers avoid unintended cross-sectoral trade-offs and synergies, leading to more cost-effective and resource-efficient governance arrangements

Greening systems by greening religion: eco-Islamic values and water-energy-nature nexus policies in Kuwait

The study examines public support for water-energy-nature (WEN) nexus policies in Kuwait, considering the interconnectedness of different natural resource sectors in addressing climate change and sustainability. While previous research has focused on technical aspects, little is known about public perceptions and willingness to adopt nexus policies. The study specifically explores the impact of moral incentives, specifically eco-Islamic values, on public support through an informational intervention. Using a randomised controlled trial (RCT) embedded in a discrete choice experiment survey, the researchers engaged a nationally representative sample of Kuwaiti residents (n=431). Participants were assigned randomly to either an informational control group or a moral incentives treatment group that emphasised eco-Islamic values. In the subsequent discrete choice experiment, participants expressed their preferences regarding three WEN nexus policy attributes: reduced emissions through renewable energy transition, increased recycled water from wastewater reduction, and tree planting for nature conservation. Results indicate that exposure to eco-Islamic values increased support for WEN nexus policies; however, while supportive, respondents do not seem willing to pay for them. These results highlight the importance of leveraging socio-cultural factors, such as religion, to promote public support for climate change action. By appealing to eco-Islamic values, policymakers can facilitate the greening of systems and ensure that religious beliefs contribute positively to efforts addressing climate change

Understanding preferences for low carbon diets and policies to address climate change in the Gulf Cooperation Council and Arab world

There is a growing consensus about the need to transition human systems and lifestyles in the Gulf Cooperation Council (GCC) and Arab nations to grapple with the challenge of environmental sustainability and climate change, while safeguarding human health and wellbeing. An important but understudied aspect of the transition is how to facilitate a shift towards low carbon diets. In this research project, we explore how socio-psychological factors influence preferences for low-carbon dietary choices and policies in the GCC and Arab world. Specifically, the study delves into the role of social norms, social referents, attitudes and beliefs on vegetarian versus non-vegetarian food choices and support for a meat tax. To do so, we use theories of social influence, the Theory of Planned Behaviour (TPB) and the Trans-Theoretical Model of Behaviour Change (TTM). We use a vignette experiment to uncover the effect of these factors on food choices, and a contingent valuation experiment to elicit willingness to accept and support a meat tax. Our initial findings reveal that social referents’ identity significantly influences dietary choices, with family and friends impacting decisions. Social occasions, such as weekends, are associated with a higher likelihood of choosing plant-based options. The research also examines support for a meat tax, indicating a substantial willingness to accept a VAT on red and processed meat. This study contributes crucial insights into the intricate interplay of cultural, social, and psychological factors shaping dietary preferences in the GCC and Arab world. The findings emphasise the importance of factoring in socio-psychological factors in designing behavioural interventions and policies to foster sustainable and health-conscious dietary practices in the region

Medusa, a multithread 4-body decay fitting and simulation software

We present a new C++14 compliant application to perform physics data analyses of generic 4-body decays in massively parallel platforms. Medusa is highly based on Hydra, a header-only library which hides most of the complexities of writing parallel code for different architectures. Medusa has been tested through the measurement of the CP-violating phase ϕsin b-hadron decays exploiting the data collected by the LHCb experiment. Medusa executes the optimization of the full model, running over 500000 events, until 330 times faster than a non-parallelized program. Medusa is freely available on GitHub under GPL v.3.0 license