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BackgroundIn U.S. states that legalized and commercialized recreational cannabis, cannabis sales in illegal markets are still sizable or even larger than those in legal markets. This study aimed to assess cannabis consumers' preferences for purchasing cannabis from legal and illegal markets and estimate the trade-offs under various policy scenarios.Methods963 adults were recruited, who used cannabis in the past year and lived in a state with recreational cannabis legalization. In a discrete choice experiment, participants chose purchasing cannabis from a legal dispensary or an illegal dealer with varying levels in product attributes including quality, safety, accessibility, potency, and price. Mixed logit models were used to analyze preferences.ResultsThe likelihood of choosing legal cannabis increased with a higher quality, the presence of lab test, a shorter distance to seller, a higher tetrahydrocannabinol level, and a lower price. The likelihood of choosing illegal cannabis increased with a higher quality, a shorter distance to seller, and a lower price. Among product attributes, quality and accessibility were perceived to be the most important for legal cannabis and price was perceived to be the most important for illegal cannabis. Policy simulations predicted that improving quality, ensuring safety, allowing delivery services, increasing dispensary density, and lowering prices/taxes of legal cannabis may reduce illegal cannabis market share.ConclusionsIn the U.S., cannabis consumers' preferences for illegal cannabis were associated with both legal and illegal cannabis product attributes. Policies regulating legal cannabis markets should consider potential spillover effects to illegal markets.

Microgreens are young plants used as ingredients and flavoring in various dishes. Their production time is short, and their production methods can be altered to enhance the nutritional content. To date, consumers’ preferences for microgreens that display different esthetic and nonesthetic traits have not been addressed. Additionally, consumers’ perceived risk of production methods used to enhance nutrition has not been investigated. An online survey and choice experiment involving a sample of 821 consumers in Tennessee were performed to investigate these topics. A mixed logit model was used to analyze the data. Both esthetic and nonesthetic traits influenced the consumers’ preferences. Green microgreens were preferred and valued more than light or dark purple microgreens. When fertilizer was used during production to enhance nutrients, consumers perceived the microgreens as riskier to the environment and for personal consumption relative to microgreens with light-induced nutrient enhancement. Using lighting during production to enhance nutrients generated a $0.47 to $0.79 premium relative to no nutrient enhancement. In general, if participants’ perceived risk aligned with the nutrient enhancement attribute (i.e., light, fertilizer), then their willingness to pay for the microgreens decreased. This was amplified for the fertilizer nutrient enhancement attribute more than it was for the light enhancement attribute. In-state production and microgreen height also impacted consumer preferences for microgreens. [ABSTRACT FROM AUTHOR]

Carbon emission reduction strategies are being implemented in the transportation sector by encouraging the adoption of eco-friendly vehicles and introducing demand management policies such as Mobility as a Service (MaaS). Nevertheless, the efficacy of MaaS in reducing carbon emissions remains uncertain. This study introduces Sustainable Public Transit (SPT) as a public transit alternative consisting of only green modes to promote sustainability. We explore the preferences of SPT in a commuting context, incorporating individual preference heterogeneity in a discrete choice model. We systematically identify the relationship between choice behaviors and individual heterogeneity in alternative attributes and psychological factors stemming from socio-demographic characteristics. The integrated choice and latent variable (ICLV) model with a mixed logit form is adopted, and the key findings can be summarized as follows: Preference heterogeneity is observed in the travel cost variable, which can be explained by characteristics such as the presence of a preschooler, household size, and income. CO2 emissions do not have a statistically significant impact on choices. Furthermore, psychological factors are also explained through socio-demographic characteristics, and it is found that low-carbon knowledge positively influences low-carbon habits. Psychological factors significantly affect choices. Respondents who dislike transfers and prioritize punctuality are less likely to choose SPT, while those who have positive low-carbon attitudes are more likely to do so. Finally, scenario analysis is conducted to forecast mode share based on improvements in SPT alternative attributes and variations in attribute levels. Policy implications are then provided to enhance the acceptability of SPT. [ABSTRACT FROM AUTHOR]

Despite the recent decline in child deaths caused by road traffic crashes in high income countries, low- and middle-income countries (LMIC) have yet to experience a similar trend. Children are among the most vulnerable of road users accounting for 30–40 % of all road traffic deaths in LMICs, 50 % of which are vehicle occupants. Previous research suggests that children ages 0–9 are the second most vulnerable age group in Ghana with 54 % of the children being fatally injured in injury-related crashes. However, little has been done to identify the associated factors influencing injury severity outcomes for child passengers in Ghana. This study investigates the factors that are associated with the various injury severity outcomes for child vehicle occupants less than 9 years old involved in road crashes in Ghana from 2014 to 2020. Results indicate that older child passengers (aged 5–8) were associated with lower injury severities compared to younger passengers. Additionally, crashes in which the driver sustained more severe injuries resulted in a higher likelihood of the child passengers sustaining a fatal injury. Findings from this research emphasize the issue of child passenger safety and support transportation policy and decision making to reduce risks of injury for child passengers.

Abstract Background In U.S. states that legalized and commercialized recreational cannabis, cannabis sales in illegal markets are still sizable or even larger than those in legal markets. This study aimed to assess cannabis consumers’ preferences for purchasing cannabis from legal and illegal markets and estimate the trade-offs under various policy scenarios. Methods 963 adults were recruited, who used cannabis in the past year and lived in a state with recreational cannabis legalization. In a discrete choice experiment, participants chose purchasing cannabis from a legal dispensary or an illegal dealer with varying levels in product attributes including quality, safety, accessibility, potency, and price. Mixed logit models were used to analyze preferences. Results The likelihood of choosing legal cannabis increased with a higher quality, the presence of lab test, a shorter distance to seller, a higher tetrahydrocannabinol level, and a lower price. The likelihood of choosing illegal cannabis increased with a higher quality, a shorter distance to seller, and a lower price. Among product attributes, quality and accessibility were perceived to be the most important for legal cannabis and price was perceived to be the most important for illegal cannabis. Policy simulations predicted that improving quality, ensuring safety, allowing delivery services, increasing dispensary density, and lowering prices/taxes of legal cannabis may reduce illegal cannabis market share. Conclusions In the U.S., cannabis consumers’ preferences for illegal cannabis were associated with both legal and illegal cannabis product attributes. Policies regulating legal cannabis markets should consider potential spillover effects to illegal markets.

In this manuscript, we propose an innovative approach to studying consumers’ preferences for coffee, which integrates a choice experiment with consumer sensory tests and chemical analyses (caffeine contents obtained through a High-Performance Liquid Chromatography (HPLC) method). The same choice experiment is administered on two consecutive occasions, i.e., before and after the guided tasting session, to analyze the role of tasting and awareness about coffee composition in the consumers’ preferences. To this end, a Bayesian optimal design, based on a compound design criterion, is applied in order to build the choice experiment; the compound criterion allows for addressing two main issues related to the efficient estimation of the attributes and the evaluation of the sensorial part, e.g., the HPLC effects and the scores obtained through the consumer sensory test. All these elements, e.g., the attributes involved in the choice experiment, the scores obtained for each coffee through the sensory tests, and the HPLC quantitative evaluation of caffeine, are analyzed through suitable Random Utility Models. The initial results are promising, confirming the validity of the proposed approach.

In a recent study, it was demonstrated that the maximum simulated likelihood (MSL) estimator produces significant biases when applied to the bivariate normal and bivariate Poisson-lognormal models. The study's conclusion suggests that similar biases could be present in other models generated by correlated bivariate normal structures, which include several commonly used specifications of the mixed logit (MIXL) models. This paper conducts a simulation study analyzing the MSL estimation of the error components (EC) MIXL. We find that the MSL estimator produces significant biases in the estimated parameters. The problem becomes worse when the true value of the variance parameter is small and the correlation parameter is large in magnitude. In some cases, the biases in the estimated marginal effects are as large as 12% of the true values. These biases are largely invariant to increases in the number of Halton draws. [ABSTRACT FROM AUTHOR]

In this manuscript, we propose an innovative approach to studying consumers' preferences for coffee, which integrates a choice experiment with consumer sensory tests and chemical analyses (caffeine contents obtained through a High-Performance Liquid Chromatography (HPLC) method). The same choice experiment is administered on two consecutive occasions, i.e., before and after the guided tasting session, to analyze the role of tasting and awareness about coffee composition in the consumers' preferences. To this end, a Bayesian optimal design, based on a compound design criterion, is applied in order to build the choice experiment; the compound criterion allows for addressing two main issues related to the efficient estimation of the attributes and the evaluation of the sensorial part, e.g., the HPLC effects and the scores obtained through the consumer sensory test. All these elements, e.g., the attributes involved in the choice experiment, the scores obtained for each coffee through the sensory tests, and the HPLC quantitative evaluation of caffeine, are analyzed through suitable Random Utility Models. The initial results are promising, confirming the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

Park and Ride (P&R) as a demand management tool has the effect of reducing traffic congestion in urban centers, saving energy and reducing pollutant emissions. Since 2000, many cities in China have been constructing P&R facilities, which have partially alleviated urban traffic congestion and provided a time-reliable mode of travel for commuters heading to urban centers. However, in recent years, due to the pricing policy of the P&R facility, there has been an insufficient supply of P&R facilities in many places. In fact, the P&R system prefers to welcome travelers who make long-distance subway rides and does not want those who make short-distance subway rides to occupy more parking spaces. To address this, this paper proposes a tiered pricing strategy that considers charging parking fees based on the distance traveled by commuters after switching to public transportation, to improve the utilization of P&R. That is, charge less for parking for long-distance subway riders and more for short-distance subway riders. Firstly, based on questionnaire data from SP surveys, a fixed pricing mixed logit model (FP model) and a tiered pricing mixed logit model (TP model) for P&R facilities are constructed. Utilizing two models, we explored the mechanisms underpinning traveler's mode choice influenced by daily habits and travel considerations through the comparison of the two models to validate the effectiveness of the tiered pricing for P&R facilities. The study found that the implementation of a tiered pricing method for P&R facilities increases its attractiveness to long-distance subway ride travelers, resulting in a higher proportion of long-distance subway riders among P&R commuters. In the study's last section, a marginal effect analysis was conducted on the per-kilometer cost (Pkm) within the P&R model. This analysis determined the optimal Pkm for three subway travel distances within the P&R model. Consequently, it calculated the corresponding P&R parking fees for these three subway travel distances. Additionally, we have predicted the implementation effects of the tiered pricing scheme. [ABSTRACT FROM AUTHOR]

Microgreens are young plants used as ingredients and flavoring in various dishes. Their production time is short, and their production methods can be altered to enhance the nutritional content. To date, consumers’ preferences for microgreens that display different esthetic and nonesthetic traits have not been addressed. Additionally, consumers’ perceived risk of production methods used to enhance nutrition has not been investigated. An online survey and choice experiment involving a sample of 821 consumers in Tennessee were performed to investigate these topics. A mixed logit model was used to analyze the data. Both esthetic and nonesthetic traits influenced the consumers’ preferences. Green microgreens were preferred and valued more than light or dark purple microgreens. When fertilizer was used during production to enhance nutrients, consumers perceived the microgreens as riskier to the environment and for personal consumption relative to microgreens with light-induced nutrient enhancement. Using lighting during production to enhance nutrients generated a $0.47 to $0.79 premium relative to no nutrient enhancement. In general, if participants’ perceived risk aligned with the nutrient enhancement attribute (i.e., light, fertilizer), then their willingness to pay for the microgreens decreased. This was amplified for the fertilizer nutrient enhancement attribute more than it was for the light enhancement attribute. In-state production and microgreen height also impacted consumer preferences for microgreens.

This paper introduces a new shifted negative log‐normal distribution for the price parameter in mixed multinomial logit models. The new distribution, labeled as the μ‐shifted negative log‐normal distribution, has desirable properties for welfare analysis and in particular a point mass that is further away from zero than the negative log‐normal distribution. This contributes to mitigating the "exploding" implicit prices issue commonly found when the price parameter is specified as negative log‐normal and the model is in preference space. The new distribution is tested on five stated preference datasets. Comparisons are made with standard alternative approaches such as the willingness‐to‐pay (WTP) space approach. It is found that the μ‐shifted distribution yields substantially lower mean marginal WTP estimates compared to the negative log‐normal specification and similar to the values derived from models estimated in WTP‐space with flexible distributions, while at the same time fitting the data as well as the negative log‐normal specification. [ABSTRACT FROM AUTHOR]

Amman, the capital of Jordan, has experienced significant traffic congestion due to the rise in private vehicle ownership and limited public transportation services. A Stated Preference (SP) survey was conducted to determine public transportation users' willingness to use the Bus Rapid Transit (BRT) service. Another survey assessed the demand for an on-demand transit bus service with flexible and moderate costs, particularly for individuals far from the main BRT stations who need to reach them. Two models, Multinomial Logit (MNL) and Mixed Logit (ML), were utilized to understand user preferences for work-related trips. The study findings indicate that the cost of the trip and the waiting time are the two primary factors influencing public transport users' choices. Furthermore, sociodemographic factors, such as age, income, household size, and current status, were found to have a significant impact. The results reveal that approximately 71% of participants would utilize an integrated public transportation system comprising BRT and on-demand services. The findings underscore the potential benefits of an integrated public transport system in addressing Amman's traffic congestion. By combining BRT and on-demand services, the city can offer residents comfortable, affordable, and efficient transportation options, thus effectively mitigating congestion. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) offer a viable technological solution for mitigating greenhouse gas emissions in the transportation industry, addressing pressing societal concerns regarding climate change, air pollution, and sustainable energy consumption. To effectively promote widespread adoption of EVs, it is crucial to understand consumer preferences and evaluate market dynamics. In Nepal, where proven fossil fuel reserves are absent, the government is actively working towards accelerating EV adoption, leveraging the nation's significant hydroelectric power generation potential to fulfill EVs' charging demands. To gain insight into consumer preferences and evaluate market dynamics regarding EVs in Nepal, this study employs a comprehensive approach. Stated preference data are collected through a meticulously designed survey, and sophisticated analytical techniques, namely, the mixed logit model and latent class model, are applied for estimation purposes. The results of this study show that potential EV consumers with small family sizes, lower monthly travel distances, heightened environmental awareness, and substantial knowledge about electric vehicles are more inclined to embrace EV technology. Notably, the study highlights that a reduction in the purchase price exerts the most significant influence on increasing consumers' likelihood of adopting battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). Market simulation results suggest that a policy mix scenario, encompassing a combination of supportive measures, proves more effective in promoting EV adoption compared to relying on single policy initiatives. Furthermore, through latent class estimation, the study identifies three distinct classes of consumers within Nepal, each exhibiting significant variations in preferences. Recognizing and addressing these variations within policy frameworks is crucial for the successful promotion and widespread acceptance of EVs in Nepal. [ABSTRACT FROM AUTHOR]

Malaysia needs to fully utilize its renewable energy resources to meet its goal of installed capacity of 31% of renewable energy in 2025 and 40% in 2035. In order to empower renewable energy sources, the government has established a fund known as the renewable energy fund (RE FUND). In Malaysia, most manufacturing sectors contribute to the RE FUND through their monthly electricity bills due to their electricity consumption exceeding 300kwh per month. As Malaysia's highest electricity consumer, the manufacturing sector needs government investment incentives to switch to renewable energy sources to generate electricity. Therefore, this study was conducted to identify attribute preferences of the manufacturing sector due to investing in renewable energy sources. The Choice Experiment method was employed where the Mixed Logit model was chosen to identify the willingness to pay for the manufacturing sectors based on their preferences among the four attributes: types of renewable energy, project location, annual reduction in GHG emissions, and RE FUND. The study results found that the manufacturing sector places the highest value on the project location, where they prefer to improve the project location from current condition to far location. This study can also help to achieve the Goal 7 in the Sustainable Development Goal (SDG), where investment in renewable energy sources can guarantee that all individuals obtain affordable, reliable, sustainable, and modern electricity in 2030.

Park and Ride (P&R) as a demand management tool has the effect of reducing traffic congestion in urban centers, saving energy and reducing pollutant emissions. Since 2000, many cities in China have been constructing P&R facilities, which have partially alleviated urban traffic congestion and provided a time-reliable mode of travel for commuters heading to urban centers. However, in recent years, due to the pricing policy of the P&R facility, there has been an insufficient supply of P&R facilities in many places. In fact, the P&R system prefers to welcome travelers who make long-distance subway rides and does not want those who make short-distance subway rides to occupy more parking spaces. To address this, this paper proposes a tiered pricing strategy that considers charging parking fees based on the distance traveled by commuters after switching to public transportation, to improve the utilization of P&R. That is, charge less for parking for long-distance subway riders and more for short-distance subway riders. Firstly, based on questionnaire data from SP surveys, a fixed pricing mixed logit model (FP model) and a tiered pricing mixed logit model (TP model) for P&R facilities are constructed. Utilizing two models, we explored the mechanisms underpinning traveler’s mode choice influenced by daily habits and travel considerations through the comparison of the two models to validate the effectiveness of the tiered pricing for P&R facilities. The study found that the implementation of a tiered pricing method for P&R facilities increases its attractiveness to long-distance subway ride travelers, resulting in a higher proportion of long-distance subway riders among P&R commuters. In the study’s last section, a marginal effect analysis was conducted on the per-kilometer cost (Pkm) within the P&R model. This analysis determined the optimal Pkm for three subway travel distances within the P&R model. Consequently, it calculated the corresponding P&R parking fees for these three subway travel distances. Additionally, we have predicted the implementation effects of the tiered pricing scheme.

In a recent study, it was demonstrated that the maximum simulated likelihood (MSL) estimator produces significant biases when applied to the bivariate normal and bivariate Poisson-lognormal models. The study’s conclusion suggests that similar biases could be present in other models generated by correlated bivariate normal structures, which include several commonly used specifications of the mixed logit (MIXL) models. This paper conducts a simulation study analyzing the MSL estimation of the error components (EC) MIXL. We find that the MSL estimator produces significant biases in the estimated parameters. The problem becomes worse when the true value of the variance parameter is small and the correlation parameter is large in magnitude. In some cases, the biases in the estimated marginal effects are as large as 12% of the true values. These biases are largely invariant to increases in the number of Halton draws.

This study proposes a data-based strategy for prioritizing sewerage services and developing consumer-centric asset management systems. Sewerage systems are essential infrastructure, but resource-intensive, and governments have faced challenges due to limited budgets and aging facilities. Most countries are still in the early stages of adopting consumer-centric approaches. By using the mixed logit model, this study identified heterogeneous service preferences among consumers based on their priority for physical and social services. Groups who attributed their importance to physical services were more sensitive to sewerage bills; however, those who emphasized social services were more interested in water activity environment improvement and odor intensity reduction. This study also showed that people are willing to pay USD 10 for odor intensity reduction and USD 6 for water activities improvement on average, but those who prioritized sinkhole reduction and flood reduction answered less willingness to pay for each service improvement. Applying these heterogeneous service preferences to service improvement strategies can lead not only to higher consumer satisfaction and lower economic burden, but also to a deeper understanding of residents' willingness to pay for service improvement in certain service preference areas. Therefore, the results contribute to the development of sustainable asset management strategies. [ABSTRACT FROM AUTHOR]

Health issues and the production of differentiated foods influence the consumers' decisions and lead them to opt for products with particular organoleptic characteristics. The objective of this research was to estimate the preferences and willingness to pay for antibiotic-free pork in the municipality of Texcoco, State of Mexico, in order to determine the existence or absence of an incentive for the commercialization of antibiotic-free pork. The Discrete Choice Method of Experiments was used. The attributes considered in the design were: color, fat content, and presence of antibiotics. A survey of 196 consumers was carried out for this purpose. The results were analyzed with the NLOGIT 4.0 software, using a mixed logit model. The most valued attribute was antibiotic content, which means that respondents would be willing to pay an additional premium of $30.65 MXN/kg for antibiotic-free pork. It was found that the higher the income and the higher the frequency of pork consumption, the greater the willingness to pay an additional premium for antibiotic-free meat. A WTP of $5.78 MXN was determined for meat with normal fat, and of $3.73 MXN for red meat. Pork consumers in the eastern part of the State of Mexico would be willing to pay an additional premium for antibiotic-free pork and for such quality aspects as fat content and color. [ABSTRACT FROM AUTHOR]

Mobility as a Service (MaaS) is often seen as a promising solution to address societal and environmental challenges. Despite the importance of quantifying its potential benefits, few previous works have focused on the impacts on the environment, and all of them considered large cities. This study aims to forecast the diffusion of MaaS in a medium-sized city and quantify the consequent reduction in pollutant emissions for commuting trips. Answers from a mobility survey administered to employees of the Municipality of Padua (Italy) were used to calibrate a model predicting MaaS adoption, which was applied to real working trips to estimate daily vehicle emissions savings in future scenarios with different MaaS bundles. The results indicated that the opportunity to have multimodal mobility options providing door-to-door travel is a fundamental element to ensure wide MaaS diffusion. Furthermore, public transport was confirmed to be the backbone of such a system. Compared to the current scenario, we observed up to a 41% reduction in pollutant emissions. The analysis pointed out that MaaS adoption is highly dependent on the characteristics of the proposed bundles, thus highlighting the importance of a proper design of the service and ex ante evaluation of emission savings. [ABSTRACT FROM AUTHOR]

Parking choice models proposed over recent years have been aimed at choosing the relevant variables and pricing policies affecting said choice. In our analyses, we have encountered some gaps to cover; for this reason, we introduce a methodology for addressing user parking choices, including the availability of parking alternatives in each of the studied zones presenting pivoted scenarios. This methodology has been developed based on a stated preferences survey design to define user behaviour when making parking choices through discrete-choice models. Furthermore, the estimated models have considered systematic and random variations in user tastes and the correlation between similar or related parking alternatives. This methodology has made it possible to provide greater realism in generating fictitious parking scenarios. The results show the importance of the fee attribute and the differences in the users' preferences depending on whether they live inside or outside the study area and their arrival time at the destination. Several scenarios have been simulated, and in these scenarios, it is found that removing free parking areas or restricting free parking in favour of parking fee regulation in congested zones can be an efficient policy measure to promote other parking alternatives and reduce the number of vehicles searching for a parking space. [ABSTRACT FROM AUTHOR]

Many studies have analyzed the road characteristics that affect the severity of truck crashes. However, most of these studies have only examined road alignment or grade separately, without considering their combined effects. The purpose of this article is to address this gap in the literature. Our study uses truck crash data from 2015 to 2019 on freeways in the Yunnan Province of China, where the severity levels of the crashes were determined by taking into account economic loss and the number of injuries and fatalities. Our study develops three models to examine the severity of truck crashes: a multinomial logit model, a mixed logit model, and a generalized ordered logit model. The findings suggest that the mixed logit model, which can suffer from unobserved heterogeneity, is more suitable because of the higher pseudo-R-squared (ρ2) value and lower Akaike Information Criterion and Bayesian Information Criterion. The estimation results show that the combination of curve and slope significantly increases the severity of truck crashes compared to curves and slopes alone. In addition, risk factors such as crash type, vehicle type, surface condition, time of day, pavement structure, and guardrails have a significant impact on the severity of truck crashes on mountainous freeways. Based on these findings, we developed policy recommendations for reducing the severity of multi-truck collisions on mountainous highways and improving transport sustainability. For example, if possible, the combination of curve and slope should be avoided. Additionally, it is recommended that trucks use tires with good heat resistance. [ABSTRACT FROM AUTHOR]

Eco-labels are crucial in helping consumers make sustainable food choices. However, previous literature has shown that eco-labels lack visibility and, frequently, are not easy for consumers to see. The main goal of the present study was to analyse the influence of aquaculture eco-labels' visual elements—size and saliency—on consumers' visual attention and choice. The study uses an eye-tracking methodology, together with a choice experiment and a semiotic analysis. A word association (WA) task was used to explore how each eco-label's graphic design influenced consumers' perceptions. Sixty-one consumers' eye movements were tracked while choosing smoked salmon and seabass products carrying different eco-labels. The results showed that size and saliency largely influence visual attention. The choice of aquaculture products was influenced only by the size of the eco-labels. According to the WA task, the shape, the symbols and the language in which the claim was written influenced consumers' preferences. The findings contribute to marketing and food research, suggesting which visual elements should be considered to increase consumers' interest in eco-labels. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) offer a viable technological solution for mitigating greenhouse gas emissions in the transportation industry, addressing pressing societal concerns regarding climate change, air pollution, and sustainable energy consumption. To effectively promote widespread adoption of EVs, it is crucial to understand consumer preferences and evaluate market dynamics. In Nepal, where proven fossil fuel reserves are absent, the government is actively working towards accelerating EV adoption, leveraging the nation’s significant hydroelectric power generation potential to fulfill EVs’ charging demands. To gain insight into consumer preferences and evaluate market dynamics regarding EVs in Nepal, this study employs a comprehensive approach. Stated preference data are collected through a meticulously designed survey, and sophisticated analytical techniques, namely, the mixed logit model and latent class model, are applied for estimation purposes. The results of this study show that potential EV consumers with small family sizes, lower monthly travel distances, heightened environmental awareness, and substantial knowledge about electric vehicles are more inclined to embrace EV technology. Notably, the study highlights that a reduction in the purchase price exerts the most significant influence on increasing consumers’ likelihood of adopting battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). Market simulation results suggest that a policy mix scenario, encompassing a combination of supportive measures, proves more effective in promoting EV adoption compared to relying on single policy initiatives. Furthermore, through latent class estimation, the study identifies three distinct classes of consumers within Nepal, each exhibiting significant variations in preferences. Recognizing and addressing these variations within policy frameworks is crucial for the successful promotion and widespread acceptance of EVs in Nepal.

Autonomous vehicles (AVs) have a number of potential advantages, although some research indicates that this technology may increase dependence on private cars. An alternative approach to bringing such technology to market is through autonomous taxis (ATs) and buses, which can assist in making transportation more sustainable. This paper aims at examining the role of attitudinal, travel-related, and individual factors in preferences for a modal shift from conventional cars toward ATs and exclusive-lane autonomous buses (ELABs), exploring the existence of heterogeneity and its possible sources. The proposed mixed logit model with a decomposition of random coefficients uses 1251 valid responses from a stated preference survey distributed in Tehran, in 2019. Results show that there is significant taste variation among individuals with respect to ATs' travel costs, ELABs' travel times, and walking distances to ELAB stations. Furthermore, exploring the sources of heterogeneity indicates that women are more sensitive to ATs' travel costs and walking distances to ELAB stations while they are less sensitive to ELABs' travel times. Moreover, travel time in discretionary activities reduces the utility of ELABs more than it does in mandatory activities. Transportation authorities can use these findings to establish more effective policies for the successful implementation of AVs. [ABSTRACT FROM AUTHOR]

The main competitor of air transportation is High-Speed Railway (HSR). However, in an oil-exporting country with low fuel prices and strong car dependence, HSR can face fierce competition with private cars and even buses. There is little previous research that forecast modal share in this situation. The case study of this research is the Tehran-Hamedan route in Iran that has high travel demand due to several historical and economic reasons and in the absence of air transportation, building the HSR in this route attracted foreign investment. To analyse the travel behaviour of passengers after the introduction of HSR, 409 stated and revealed preferences were collected in a self-designed questionnaire. Multinomial logit (MNL) model and mixed logit (ML) model were developed and modal share of each mode of transportation were forecasted up to 2045. HSR modal share is compared with other routes of the world to see the impact of air competition. The overall modal share of railway in this route is estimated to reach 64%, which is close to the average of major HSR routes globally (around 60%). Therefore, private cars can be a fierce competitor for HSR when there is no air link on the route and fuel is rather cheap.

Spatial perceptions mediate human–environment interaction, and understanding spatial perceptions of humans can play a key role in the planning of activities. This study aims to analyze spatial multivariate binary choice data representing if an individual perceives a spatial unit to belong to a certain category (e.g. , her neighborhood or set of potential activity places). To reasonably analyze such data, we present a spatial autoregressive mixed logit (SAR-MXL) model that accounts for both inter-individual heterogeneity and spatial dependence. We rely on the Bayesian approach for posterior inference of model parameters, where Pólya-Gamma data augmentation (PG-DA) is adopted to address the non-conjugacy of the logit kernel. The PG-DA technique eliminates the need for the Metropolis–Hastings step during the Markov Chain Monte Carlo process and allows for fast and efficient posterior inference. The high efficiency of the Bayesian SAR-MXL model is demonstrated through a numerical experiment. The proposed framework is applied to street-based neighborhood perception data, and we empirically analyzed the factors associated with the street perception probability of individuals. The result suggests a clear improvement of the model fit by incorporating spatial dependence and random parameters. • We study spatial multivariate binary choice data representing spatial perception. • We explicitly consider spatial dependence and individual taste heterogeneity. • We develop a hierarchical Bayesian spatial autoregressive mixed logit model. • We apply Pólya-Gamma data augmentation to address the non-conjugacy issue. • We analyze neighborhood perception and reveal strong spatial dependence based on street network topology. [ABSTRACT FROM AUTHOR]

Low-density areas like suburbs can be challenging to serve with fixed-route transit. Demand responsive transit has been used to service these areas with mixed results, but suburban travellers may respond to ridesourcing integrated with transit more positively because of the improved booking and dispatching interface offered by ridesourcing. This paper explores how suburban residents perceive transit-integrated ridesourcing, both for cost and time attributes of the system and in comparison to other travel modes in the area (cycling, auto, taxi or Uber, and transit). A Hierarchical Bayes mixed logit model was estimated using the results of a revealed-preference/stated-preference survey, revealing that transit-integrated ridesourcing had similar preferences to fixed-route transit. Across time and cost variables, respondents were more sensitive to walk time, transfer time, the number of transfers, parking cost, and taxi or Uber fare, and were minimally impacted by changes in the IVTT deviation of their trip times. The change in utility for the length of transit or transit-integrated ridesourcing in-vehicle travel time versus auto in-vehicle travel time was found to have a strongly linear relationship, while other attributes exhibited non-linearity to different degrees, particularly walk time, transfer time, transit-integrated ridesourcing fare, and taxi or Uber fare. Respondents who were female, younger, taking home-based school trips, or had lower household incomes were more open to transit-integrated ridesourcing and transit than other demographic groups. The likelihood of taking each of the five travel modes was assessed after COVID-19, finding generally minimal to negative impact for transit-integrated ridesourcing. Insights into vehicle and transit pass ownership, existing travel alternatives, and a prior transit-integrated ridesourcing pilot in the area are presented.

This study aims to analyze farmers’ willingness to contribute labor for the ongoing natural resource rehabilitation interventions in watershed development in East and West Belesa Districts, Amhara region. The aim of the study to assesses farmers’ intervention in natural resource rehabilitation activities and examines the mean willingness to pay family labor required for public watershed development activities from the two districts; a total of 501 households were selected by using a multistage sampling technique. The collected data were analyzed using a descriptive and econometrics model. In the econometric part, the mixed logit model is used to analyze the mean willingness to contribute to family labor. The descriptive result showed that farmers have to improve the watershed ecosystem service through soil and water conservation, area enclosure, forestation, and reforestation natural resource management intervention methods. The mean willingness to pay contribution results from the mixed logit, revealing that the sampled households are willing to contribute for livestock fodder availability 0.79 labors per month means Farmer’s Contribute 8 daily labors per months for watershed management activity for stabilizing spring water flow 0.80 labors per month, for reduced soil erosion 0.14 labors per month, and increase crop productivity 0.09 labors per month, respectively. The results important for policymakers and extension workers not to expect all farmers’ have homogeneous daily labor contribute to public watershed development activity.

Discrete location, occupation, skill, and hours choices of workers underpin their incomes. This paper analyzes the optimal taxation of discrete income‐generating choice. It derives optimal tax equations and Pareto test inequalities for mixed logit choice environments that can accommodate discrete and unstructured choice sets, rich preference heterogeneity, and complex aggregate cross‐substitution patterns between choices. These equations explicitly connect optimal taxes to societal redistributive goals and private substitution behavior, with the latter encoded as a substitution matrix that describes cross‐sensitivities of choice distributions to tax‐induced utility variation. In repeated mixed logit settings, the substitution matrix is exactly the Markov matrix of shock‐induced agent transitions across choices. We describe implications of this equivalence for evaluation of prevailing tax designs and the structural estimation of optimal policy mixed logit models. We apply our results to two salient examples: spatial taxation and taxation of couples. [ABSTRACT FROM AUTHOR]

ObjectiveThis study aims to identify all actors that hold some responsibility for ensuring food safety based on the complete food supply chain in the context of China's current circumstances.MethodsThe study was conducted among citizens in Wuxi, Jiangsu, China. All citizens fully understood the purpose of the study and voluntarily agreed to participate. From December 10 to 14, 2020, a total of 398 valid samples were collected by the researchers using a structured questionnaire. Survey data were assessed using best–worst scaling and a mixed logit model from the perspective of citizen responsibility.ResultsIn descending order, responsibility for ensuring food safety goes from food producers and traders (including producers, distributors, and retailers) to the government, social organizations, news media, and finally to citizens. Food producers and traders are the actors who should take the greatest responsibility, whereas citizens bear the least responsibility.ConclusionThe responsibility of citizens in food safety co-governance should be recognized but it should not be arbitrarily extended.

This study proposes a data-based strategy for prioritizing sewerage services and developing consumer-centric asset management systems. Sewerage systems are essential infrastructure, but resource-intensive, and governments have faced challenges due to limited budgets and aging facilities. Most countries are still in the early stages of adopting consumer-centric approaches. By using the mixed logit model, this study identified heterogeneous service preferences among consumers based on their priority for physical and social services. Groups who attributed their importance to physical services were more sensitive to sewerage bills; however, those who emphasized social services were more interested in water activity environment improvement and odor intensity reduction. This study also showed that people are willing to pay USD 10 for odor intensity reduction and USD 6 for water activities improvement on average, but those who prioritized sinkhole reduction and flood reduction answered less willingness to pay for each service improvement. Applying these heterogeneous service preferences to service improvement strategies can lead not only to higher consumer satisfaction and lower economic burden, but also to a deeper understanding of residents’ willingness to pay for service improvement in certain service preference areas. Therefore, the results contribute to the development of sustainable asset management strategies.

This paper aims to analyse to what extent the willingness to pay of art gallery visitors for the preservation of cultural artefacts is affected by the identity traits of the objects. To this purpose, we designed a discrete choice experiment that took place during a major exhibition dedicated to the artist Costantino Nivola (1911–1988) in Sassari (Sardinia, Italy). His works are known worldwide and many of them were produced after he moved from Sardinia to the United States in 1939. As a result, both the American and the Sardinian culture show up in his works and, in particular, were clearly visible in the exhibition under study. The discrete choice experiments allowed us to elicit respondents' preferences towards the identity features stemming from Nivola's artefacts. The results confirm the importance of this component indicating that its presence almost doubles respondents' willingness-to-pay for the acquisition of these artefacts to a permanent collection. [ABSTRACT FROM AUTHOR]

This study estimates the economic value of local environmental amenities in Bahir Dar city which is one of the tourist attraction sites in Ethiopia. The study employed choice experiment valuation method by identifying four environmental amenities attributes (Lake Tana, urban park, palm tree and street cleanliness). The study used probability multi-stage random sampling technique. The analysis was based on primary data surveyed from households in Bahir Dar city. The study presented nine choices set for each respondent; each choice set has three alternatives including the status quo option. The study employed a mixed logit model. The result showed that all improved attribute levels have positive signs and statistically significant. As expected and consistent with economic theory the monetary cost has negative signs and significant. The mixed logit model showed that there is preference heterogeneity in some attribute levels. Based on the finding, the study recommends that the city administration and the concerned body expected to implement the hypothetical policy scenario so as to improve environmental amenity.

• A methodological framework to define conflict risk and level of severity during overtaking maneuver using surrogate measures for two-lane two-way highway in non-lane based heterogeneous traffic environment has been outlined. • A number of different models based on the discrete choice modelling approach have been explored to assesses the overtaking conflict risk severity. • The combined role of correlation in the unobserved factors over the alternatives outcomes, fixed threshold, and unobserved heterogeneity effects of different exogenous factors across observations are assessed. • A large set of explanatory variables pertaining to overtaking maneuver in two-lane two-way highway with non-lane based heterogeneous traffic environment are examined; • Several performance measures are used to assist the performance the model evaluation task; and. • A discussion is included with the illustration of the practical applicability of the proposed overtaking maneuver risk modeling framework. Introduction: Driver behavior related to overtaking maneuvers, which are considered a major safety risk determinant on two-lane two-way highway in low- and middle-income countries (LMIC), are an important subject of further analysis. This study evaluates safety risk in terms of nature and severity of probable conflicts during overtaking maneuvers on a bi-directional undivided two-lane highway in a heterogeneous traffic environment of a low-income country. Nature and severity of probable conflicts were defined with the application of surrogate safety proximity indicators in real-world naturalistic driving environment. Method: A risk severity model for overtaking maneuver was developed to better understand the significant factors associated with the probability of conflict and its severity during overtaking maneuver using discrete choice modeling approaches. The relevance of three alternate discrete outcome frameworks, namely multinomial logit (ML), ordered probit (OP), and mixed logit (MXL) models are addressed. The best fitted model is identified and estimated. The impact of the significant attributes was also evaluated. The study collected data from a section of two-lane highway in Bangladesh using naturalistic driving from both observational and computer vision techniques. A total of 46 explanatory variables related to overtaking maneuver are assessed. Results: Speed differential between overtaking and overtaken vehicles have a significant impact on the probability of severe conflicts. Moreover, the presence of a bus as an overtaking vehicle was found to contribute significantly to the severity of conflicts. Conclusions: The study makes substantial research contributions related to overtaking behavior and safety risk evaluation during overtaking in mixed traffic environment in low-income countries. The results can be used as a proactive tool for the evaluation of overtaking maneuvers and associated safety risk, and making policy decisions reducing safety risk during overtaking maneuver as well as overall safety, while acknowledging the limited resources and facilities in low-income countries. [ABSTRACT FROM AUTHOR]

Discrete choice experiments are widely used in a broad area of research fields to capture the preference structure of respondents. The design of such experiments will determine to a large extent the accuracy with which the preference parameters can be estimated. This paper presents a new R package, called idefix, which enables users to generate optimal designs for discrete choice experiments. Besides Bayesian D-efficient designs for the multinomial logit model, the package includes functions to generate Bayesian adaptive designs which can be used to gather data for the mixed logit model. In addition, the package provides the necessary tools to set up actual surveys and collect empirical data. After data collection, idefix can be used to transform the data into the necessary format in order to use existing estimation software in R.

Improving the service quality of public transport is necessary to maintain the loyalty of current users and attract new travelers. Past studies show that users' preferences for transit service quality are heterogeneous, but recognizing the factors describing this heterogeneity has not been investigated in depth. This paper aims to evaluate the sources of heterogeneity in passengers' preferences for service attributes of bus transit regarding the regular bus system in the city of Tehran. Four attributes of bus travel, including in-vehicle travel time, fare, vehicle crowding, and headway, were considered. Stated preference (SP) data of 360 commuters with work purpose was collected through face-to-face interviews. The random parameter logit (RPL) model, considering the heterogeneity around the mean of random coefficients, shows that heterogeneity can be explained to some extent by observed characteristics. It can be helpful for transit operators to adopt more efficient measures to improve service aspects. [ABSTRACT FROM AUTHOR]

This study aims to analyze farmers' willingness to contribute labor for the ongoing natural resource rehabilitation interventions in watershed development in East and West Belesa Districts, Amhara region. The aim of the study to assesses farmers' intervention in natural resource rehabilitation activities and examines the mean willingness to pay family labor required for public watershed development activities from the two districts; a total of 501 households were selected by using a multistage sampling technique. The collected data were analyzed using a descriptive and econometrics model. In the econometric part, the mixed logit model is used to analyze the mean willingness to contribute to family labor. The descriptive result showed that farmers have to improve the watershed ecosystem service through soil and water conservation, area enclosure, forestation, and reforestation natural resource management intervention methods. The mean willingness to pay contribution results from the mixed logit, revealing that the sampled households are willing to contribute for livestock fodder availability 0.79 labors per month means Farmer's Contribute 8 daily labors per months for watershed management activity for stabilizing spring water flow 0.80 labors per month, for reduced soil erosion 0.14 labors per month, and increase crop productivity 0.09 labors per month, respectively. The results important for policymakers and extension workers not to expect all farmers' have homogeneous daily labor contribute to public watershed development activity. [ABSTRACT FROM AUTHOR]

Abstract Background User fees, transportation costs, and time costs impair access to healthcare by rural communities in low and middle income countries. However, effects of time costs on demand for healthcare are less understood than effects of user fees for health providers. In addition, prospective patients might not know about all health services available. This study aims to investigate how the family caregivers of febrile children respond to the pecuniary costs and time costs in their choice of health providers in rural Papua New Guinea. Methods Using an original questionnaire, we surveyed households in the catchment area surrounding Dagua Health Center in East Sepik Province, Papua New Guinea, during February–March 2015. We estimated the probability of choosing one among four categories of providers (i.e., the health center, aid posts, village health volunteers [VHVs], or home-treatment) via a mixed logit model in which we restrict alternatives to those for which family caregivers knew cost information. Results Of 1173 family caregivers, 96% sought treatment for febrile children from four categories of providers. Almost all knew the location of the health center and a health volunteer, but only 50% knew the location of aid posts. Analysis by discrete choice model showed that pecuniary costs and time costs were inversely associated with the probability of choosing any type of provider. We then changed pecuniary costs and time costs counterfactually to calculate and compare the probability of choosing each provider. Time costs affected the choice more than pecuniary costs, and individual heterogeneity appeared among caregivers with respect to pecuniary costs. When pecuniary or time costs of VHVs are altered, substitution between VHVs and home-treatment appeared. Conclusions Our findings suggest that policies to increase awareness of aid posts and reduce time costs in addition to treatment fees for each category of healthcare provider could help developing economies to improve access to essential healthcare services.

Foods with "clean labels," that is, foods with few ingredients, may mitigate the stigma from the lack of healthfulness in processed food products. However, with conventional technologies, clean labels are difficult to achieve. We conducted a survey, including choice experiment scenarios, in which half of the respondents were presented scenarios to purchase a shelf‐stable ready meal with a clean label/fewer ingredients, and the other half were presented scenarios including the clean label/fewer ingredients and a new technology that allows for processed foods to be produced with fewer ingredients. In general, respondents were willing to pay a price premium for the clean label and the new food technology used. However, such preferences were heterogeneous. In the version of the survey that did not include the type of technology, the classes were "clean label incredulous," "moderate believers in clean labels," and "strong believers in clean labels." In the survey version including the type of technology, the classes were "clean label indifferent and technology takers," "moderate believers in clean labels and technology indifferent," and "strong believers in clean labels and technology indifferent." Our findings underscore the importance of providing consumers with information about a new technology and the resulting benefits to reduce perceived risks and increase consumer acceptance. [ABSTRACT FROM AUTHOR]

There is increasing interest in accessing local food products through 'conventional' food marketing systems. This study identifies and quantifies key contract characteristics and buyer attributes valued by small-scale produce farmers who are currently or are considering marketing into wholesale channels. Overall, produce farmers are receptive to entering into contracts with wholesale buyers. Substantial heterogeneity, however, is found among farmer attitudes toward the specific contract terms and in the trade-offs farmers are willing to accept between contract terms and buyer characteristics. Insights offered will enable produce buyers to more efficiently target potential suppliers and will facilitate more effective contract design.

Abstract Background There is a substantial interest in the values that consumers place on drinking water quality and supply. Financial resources are crucial to improving the urban potable water supply in developing countries that are characterized by low-cost recovery rates and a high and rapidly growing demand for more reliable services. This study examined households’ willingness to pay (WTP) for the improvement of water services by identifying their water choice decisions and the mode of water supply that they prefer the water supply authority to use among several alternative water supply options. Stated-preference data were collected from 322 randomly selected households in Addis Ababa, who were presented with three sets of choices (three alternative bundle choices, including the reference scenario). The data were analyzed using the mixed logit WTP space model. Three approaches to modeling the distribution of WTP (fixed, uncorrelated, and correlated) using mixed logit WTP space models were compared. Results Three-quarters of the households agreed to contribute money toward ecosystem-based water supply management (EBWSM) intervention programs on a monthly basis. The average contribution that the respondents were willing to pay was 150.5 Ethiopian Birr (ETB) as a one-off lump sum to kick off the EBWSM activities. Most of the respondents chose a bundle of water supply options that provides risk-free and high-quality water with no months of shortages than moderate water quality that is safe to drink and palatable with 1 month shortages annually. This implies that households would need to be supplied with risk-free, high-quality water without interruption at an appropriate flow pressure. The model with correlations fitted the data well with the highest simulated log-likelihoods at convergence and gave the best estimate of the households’ WTP for water improvement. Nearly 46% of the sampled households were willing to pay more than 33 ETB per month, and 49% of the households were willing to pay between 21 ETB and 33 ETB per month for the monthly water bill. Overall, approximately 95% of the sampled households were willing to pay more than 21 ETB. Conclusion Customers are willing to pay to avoid most types of water supply restrictions. Moreover, WTP is sensitive to the scope of service improvement, income, affixed price, and elicitation method. In summary, mixed logit WTP-space models can help accurately predict household-level WTP, which can be used to select improvements in drinking water access and services in the Legedadie-Dire catchments.

Ghana’s National Agricultural Research Systems have officially released 24 improved cassava varieties, which are high yielding, disease and pest resistant and early maturing. However, adoption of these varieties by mainly smallholder farmers is very low, leading to low yields and incomes. The purpose of this study was to contribute to the development and adoption of improved cassava varieties by assessing the preferences of farmers for cassava variety traits. The study explored Ghanaian cassava producers’ decision-making behaviour towards variety selection and the values they place on different cassava traits. It employed mixed logit and latent class models to estimate the values place on cassava traits, by using choice experiment data of 450 cassava producers from Ghana. Results revealed farmers’ preferences for longevity of root storage in the soil and disease resistance traits of cassava. The latent class model revealed that male youths were more likely to participate in improved varieties that take into account in-soil storage and multiple usages. The need for agricultural research systems to focus on other traits in addition to high yielding and disease resistance in order to boost adoption and increase production is imperative.

Farmers inevitably make trade-offs when choosing which crop varieties to grow based on each variety's unique strengths (and weaknesses). This study uses choice experiment data from 1288 maize farmers from western Kenya and applies a mixed logit model to estimate willingness to sacrifice yield as an experimental devise to measure such trade-offs when farmers are called upon to chose varieties with varying levels of desirable agronomic or consumption traits. We find that men and women respondents had similar preferences for maize traits, but differed in the rate of tradeoffs between traits. Women respondents appeared to make larger yield sacrifices for tolerance to drought, Striga weed and good storability than men. Men showed higher willingness to sacrifice yield for closed tip. Implications for gender-sensitive maize breeding and seed market development are drawn.

This study estimates the economic value of local environmental amenities in Bahir Dar city which is one of the tourist attraction sites in Ethiopia. The study employed choice experiment valuation method by identifying four environmental amenities attributes (Lake Tana, urban park, palm tree and street cleanliness). The study used probability multi-stage random sampling technique. The analysis was based on primary data surveyed from households in Bahir Dar city. The study presented nine choices set for each respondent; each choice set has three alternatives including the status quo option. The study employed a mixed logit model. The result showed that all improved attribute levels have positive signs and statistically significant. As expected and consistent with economic theory the monetary cost has negative signs and significant. The mixed logit model showed that there is preference heterogeneity in some attribute levels. Based on the finding, the study recommends that the city administration and the concerned body expected to implement the hypothetical policy scenario so as to improve environmental amenity. [ABSTRACT FROM AUTHOR]

Invasive mammals are a primary threat to New Zealand's endemic species. In remote areas, aerial delivery of poison is the preferred method of pest management, although it faces some public backlash. Novel pest control technologies are currently being investigated as alternatives but may face similar concerns. To investigate potential social and demographic determinants of public perceptions of new methods for pest control, we conducted a national choice experiment, focused on several novel technologies: gene drives, Trojan females, and species-specific poisons. We found that preferences strongly depend on the type of technology, with Trojan female technology strictly preferred to the other two. Although several characteristics affected preferences in predictable ways--education, trust in science, and liberal political leaning increased acceptance--the same did not hold with preferences for aerial delivery. Our results are useful for targeting future engagement campaigns and leveraging existing efforts. [ABSTRACT FROM AUTHOR]