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This paper reports the results of a stated preference survey of regular transit users’ willingness to ride and concerns about driverless buses in the Philadelphia region. As automated technologies advance, driverless buses may offer significant efficiency, safety, and operational improvements over traditional bus services. However, unfamiliarity with automated vehicle technology may challenge its acceptance among the general public and slow the adoption of new technologies. Using a mixed logit modeling framework, this research examines which types of transit users are most willing to ride in driverless buses and whether having a transit employee on board to monitor the vehicle operations and/or provide customer service matters. Of the 891 surveyed members of University of Pennsylvania’s transit pass benefit program, two-thirds express a willingness to ride in a driverless bus when a transit employee is on board to monitor vehicle operations and provide customer service. By contrast, only 13% would agree to ride a bus without an employee on board. Males and those in younger age groups (18–34) are more willing to ride in driverless buses than females and those in older age groups. Findings suggest that, so long as a transit employee is onboard, many transit passengers will willingly board early generation automated buses. An abrupt shift to buses without employees on board, by contrast, will likely alienate many transit users.

We estimate the economic benefits of avoiding reductions in drinking water quality due to sea level rise accruing to North Carolina (NC) coastal tourists. Using stated preference methods and responses from recent coastal visitors, we find that tourists are 2%, 8%, and 11% less likely to take an overnight trip if drinking water tastes slightly, moderately, or very salty at their chosen destination. The majority of those who decline a trip would take a trip to another NC beach without water quality issues, others would take another type of recreational trip, with a minority opting to stay home. Willingness to pay for an overnight beach trip declines with the salty taste of drinking water. We find evidence of attribute non‐attendance in the stated preference data, which impacts the regression model and estimates of the willingness to pay for trips. Combining economic and hydrological models, annual aggregate benefit losses due to low drinking water quality could be as high as$232 million by 2040. Key Points We estimate the benefits to North Carolina coastal tourists of avoiding reductions in drinking water quality due to sea level rise Willingness to pay for an overnight beach trip declines with the salty taste of drinking water Annual aggregate benefit losses due to low drinking water quality could be as high as $ 232 million in 2040

Stated preference (SP) methods are increasingly being applied to HIV-related research and continuously provide researchers with health utility scores of select healthcare products or services that populations consider important. Following PRISMA guidelines, we sought to understand how SP methods have been applied in HIV-related research. We conducted a systematic review to identify studies meeting the following criteria: SP method is clearly stated, conducted in the United States, was published between 01/01/2012 and 02/12/2022, and included adults aged 18 and over. Study design and SP method application were also examined. We identified six SP methods (e.g., Conjoint Analysis, Discrete Choice Experiment) across 18 studies, which were categorized into one of two groups: HIV prevention and HIV treatment-care. Categories of attributes used in SP methods largely focused on: administration, physical/health effects, financial, location, access, and external influences. SP methods are innovative tools capable of informing researchers on what populations consider most beneficial when deciding on treatment, care, or prevention options for HIV.

The outcome of a conservation policy is often subject to uncertainty. In stated preference valuation, it is increasingly recognised that uncertainty affects preferences for the outcomes of environmental policies. However, there is also agreement that the effect of uncertainty and people’s attitudes towards risk need to be better understood. To shed more light on the impact of risk, we designed a discrete choice experiment to compare preferences for environmental outcomes under climate change across two split samples. Each sample was confronted with a scenario where results were presented as certain or uncertain, but were otherwise associated with the same expected values. We found significant differences between the certain and the uncertain treatment, with uncertain outcomes being associated with more extreme utility levels and willingness to pay, in absolute terms. This finding was confirmed irrespective of whether gains or losses were considered and despite sensitivity to uncertainty—specific to the socio-demographic profile. Our results suggest that individuals are not risk neutral in the presence of uncertainty around environmental outcomes. These findings are crucial to better understand stated preferences for conservation policies in risky contexts. Our results reinforce the idea that uncertainty should be explicitly incorporated in the design of stated preference studies to better inform policy.

Transdisciplinary projects can uncover crucial insights on people’s past and future risk-mitigation behavior. We focus on a novel risk context: increasing health threats from ticks on Staten Island, a New York City borough where the combination of high population density and extensive park systems and green spaces has resulted in a rise in locally-acquired tick-transmitted disease cases. We administered a knowledge, attitudes, and practices survey that additionally included simple economic stated preference questions about people’s willingness to spray tick pesticides in the future. We first analyze factors that are correlated with people’s perceptions of two types of risks: exposure to ticks and infection with Lyme disease. Next, we use the nonmarket valuation questions to test people’s willingness to spray and pay as a function of attributes of the hypothetical pesticides, including cost, effectiveness, and type. Across all model specifications, overall willingness to pay (WTP) to spray increases with increases in pesticide effectiveness, as well as with favorable pesticide type (organic). We uncover threshold pesticide effectiveness levels at which WTP to spray turns positive, and we find that lower pesticide effectiveness is required for organic pesticide. Finally, we test how perceived risks and various individual-specific characteristics correlate with WTP to spray. Combinations of higher perceived risks are linked both with higher WTP and lower breakeven pesticide effectiveness. Our work shows that a broad range of variables influence demand for self-protection actions, both directly and indirectly (through their effects on perceived risks). Such insights on people’s tradeoffs carry important policy implications, but they can be missed if economic information is either not elicited or elicited alone.

The increased use of renewable energy is imperative as a countermeasure to climate change. As with conventional electricity generation technologies, public acceptance of renewables is an important issue, and willingness to pay (WTP) is a widely used indicator to assess such public attitudes. Unfortunately, the literature to date mostly covers developed countries, with few WTP surveys in developing countries. Tackling climate change is an urgent issue for these developing countries; therefore, understanding of public attitudes toward renewables in developing countries is crucial. This study conducted the first survey on WTP for introducing renewable energy in Myanmar. Although Myanmar boasts abundant renewable energy resources, including solar power and biomass in addition to large-scale hydro plants, its resources are not being properly utilized to generate electricity. This study surveyed WTP for power generation by solar photovoltaics, small hydropower, and biomass facilities. The results showed the highest WTP for solar power (USD 1.92) with 10% share in the energy mix, and lower WTP for biomass and small hydropower electricity generations (USD 1.13 and USD 1.17, respectively). Careful public communication is thus crucial for expanding biomass and small-scale hydro power plants.

The treatment of the opportunity cost of travel time in travel cost models has been an area of research interest for many decades. Our analysis develops a methodology to combine the travel distance and travel time data with respondent-specific estimates of the value of travel time savings (VTTS). The individual VTTS are elicited with the use of discrete choice stated preference methods. The travel time valuation procedure is integrated into the travel cost valuation exercise to create a two-equation structural model of site valuation. Since the travel time equation of the structural model incorporates individual preference heterogeneity, the full structure model provides a travel cost site demand model based upon individualized values of time. The methodology is illustrated in a study of recreational birdwatching, more specifically, visits to a ‘stork village’ in Poland. We show that the usual practice of basing respondents’ VTTS on 1/3 of their wage rate is largely unfounded and propose alternatives—including a separate component of the travel cost survey aimed at valuation of respondents’ VTTS or, as a second best, asking if they wish if their journey was shorter and for those who do—use full hourly wage as an indicator of their VTTS.

In the US, the rise in motorized vehicle travel has contributed to serious societal, environmental, economic, and public health problems. These problems have increased the interest in encouraging non-motorized modes of travel (walking and bicycling). The current study contributes toward this objective by identifying and evaluating the importance of attributes influencing bicyclists’ route choice preferences. Specifically, the paper examines a comprehensive set of attributes that influence bicycle route choice, including: (1) bicyclists’ characteristics, (2) on-street parking, (3) bicycle facility type and amenities, (4) roadway physical characteristics, (5) roadway functional characteristics, and (6) roadway operational characteristics. The data used in the analysis is drawn from a web-based stated preference survey of Texas bicyclists. The results of the study emphasize the importance of a comprehensive evaluation of both route-related attributes and bicyclists’ demographics in bicycle route choice decisions. The empirical results indicate that travel time (for commuters) and motorized traffic volume are the most important attributes in bicycle route choice. Other route attributes with a high impact include number of stop signs, red light, and cross-streets, speed limits, on-street parking characteristics, and whether there exists a continuous bicycle facility on the route.

The rapid development of autonomous vehicles (AV) in recent years has drawn the attention of numerous countries in terms of its feasibility for use and deployment as individually-owned vehicles or for large-scale fleet planning and deployment as a mobility-on-demand (MOD) service. Singapore is no exception to this global trend and in her pursuit to be smart and car-lite, numerous efforts are made to have AV trials in place and test out their potential deployment in the city state. As one of the many prerequisites of AV planning, public perception on AV plays a vital role when designing any potential AV deployment scheme. As such, a stated preference survey comprising both online survey and field interviews/surveys, was performed island-wide to understand how commuters in Singapore perceive about different AV-based MOD modes. The logit kernel model is adopted to determine how different preference attributes and key demographic indicators can affect the use of AV-based MOD services over other existing first- and last-mile connection modes. The model results have identified how demographics such as gender, age, housing type, education level and income level can influence the travel mode choice. Also, the impacts brought by individuals’ stated preferences over convenience, privacy and familiarity of ride-hailing apps are also investigated. Such findings can provide useful insight in planning future car-lite towns and implementing AV-based MOD services in these towns.

Despite all the promising benefits, the adoption of fully autonomous vehicles (FAVs) is expected to require a long transitional process. While innovators and early adopters tend to adopt the technology fast, most will gradually adopt the technology after varying periods. Meanwhile, today’s social networking technologies have strengthened the influence of peer effects and caused noticeable changes to decision-making behavior. To date, there is relatively little study on how peer effects influence autonomous vehicles (AVs) adoption. The current paper explores how AV adoption is influenced by various factors, especially by different levels of individual susceptibility and prior-AV knowledge. Susceptibility is a latent variable measuring to what extent individuals will follow the influence of their peers in AV adoption. Prior-AV knowledge is another latent variable that measures people’s knowledge about AVs, which will further impact their price sensitivity. A stated preference (SP) survey was carried out in five cities in China. 1132 new car buyers were surveyed, resulting in 3855 valid records for vehicle preference. The Integrated Choice and Latent Variable (ICLV) Model is used to measure the susceptibility and prior-AV knowledge attributes, and identify their contribution to the heterogeneity of AV adoption intentions. The results show that many demographic factors influence the adoption of AVs. Younger individuals, those with higher education levels, higher income, and more driving experience are more readily influenced by their peers. High market penetration has a significant influence on FAV adoption, but to a varying degree depending on the individual susceptibility level. People with prior-AV knowledge, who are more likely to be older drivers, have no children under 18, have higher incomes and higher education levels, are found to be less sensitive to vehicle price.