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Endogenous regressors can lead to biased estimates for causal effects using methods assuming regressor–error independence. To correct for endogeneity bias, the authors propose a new method that accounts for the regressor–error dependence using flexible semiparametric odds ratio conditional models; the approach requires neither parametric distributional assumptions nor tuning parameters for modeling endogenous regressors' distributions conditional on the error term and exogenous regressors. Inference is achieved via optimizing the profile likelihood concentrating on the parameters of interest. The proposed approach requires no use of instrumental variables (IVs), observed or latent, that must satisfy the stringent condition of exclusion restriction. Nonnormally distributed endogenous regressors are required for model identification with a normal error distribution. The approach's flexibility in capturing regressor–error dependence increases the capability of IV-free endogeneity correction and provides opportunities to improve the accuracy of causal effect estimation. Unlike existing IV-free methods, the proposed approach can handle discrete endogenous regressors with few levels, such as binary regressors or count regressors with small means, and is thus applicable to a plethora of applications involving such regressors. The authors demonstrate the versatility of the approach for binary, count, and continuous endogenous regressors using comprehensive simulation studies and empirical data. [ABSTRACT FROM AUTHOR]

A considerable share of farmland market activity is related to non-agricultural owners. Recent research has shown that those non-agricultural owners are likely to be private persons. However, little is known about potential factors which drive their decision to invest in farmland. This study aims to investigate four groups of factors which could affect the decision of non-agricultural persons to buy farmland: Key investment information, financial knowledge, the attitude towards money, and sociodemographic characteristics. Primary discrete choice data, which is representative for our study region Germany within four categories, has been collected for the purpose of this study. 637 participants were asked to invest in farmland, financial products or save their money in a bank account. A mixed logit approach revealed, that variables from each factor group are related to the decision to invest in farmland. According to the effect sizes, risk (volatility of returns), returns, a university degree and a preference for a secure investment performance are especially important factors for investment decisions. Furthermore, considerable differences exist between people with a high financial literacy score or a high level of self-assessed financial knowledge. [ABSTRACT FROM AUTHOR]

AbstractThis study explores the role of mobility platforms in mitigating issues arising from information asymmetry about taxi services in South Korea. We employed conjoint analysis from a cognitive fit perspective and analyzed the marginal utilities of platform features using a mixed logit model. Our results show that platformization addresses negative experiences associated with information asymmetry and resolves long-standing problems associated with taxi services. Specifically, consumers prioritize information visualization and safety services, underscoring the platforms’ role in enhancing trust and safety as well as convenience. Despite the expansion into premium mobility experiences, the fundamental expectation from consumers remains access to reliable, safe services. This research contributes to understanding the impact of digital transformation on the mobility sector, emphasizing the need for strategic and policy interventions to leverage mobility platforms for improved service delivery. [ABSTRACT FROM AUTHOR]

Pre-peak fare discount policies have become increasingly common in urban transit services and show potential to spread morning peak-hour demand. This study analyzes the departure time choice behavior of interregional bus passengers during morning hours. A mixed logit model is applied to estimate the probability of shifting departure time as a function of fare discount rate, in-vehicle congestion, and other influential factors, accommodating heterogeneity of passenger preferences. The analysis data are obtained through a stated preference survey, which is conducted to passengers who regularly use the interregional bus in Seoul metropolitan area. Choice models are segmented by departure time periods (peak, pre-peak, and post-peak) and occupation types (fixed time worker, flexible time worker, and student). Marginal utilities of the unobserved preferences are estimated to suggest policy implications. From the experimental analysis, target passengers for shifting departure time during peak hour are suggested as flexible time workers and students. [ABSTRACT FROM AUTHOR]

This study examines smallholder farmers' preferences and willingness to pay for an improved irrigation water supply program in northwest Ethiopia. We employed a discrete choice experiment with five attributes and three levels. Data were collected from randomly selected sample households of both irrigation users and non-users. A total of 379 respondents participated, and a mixed logit model was used to analyze the household-level survey data. The result indicates that to deviate from the business-as-usual scenario, smallholder farmers are willing to pay between 3,228 and 8,327 Ethiopian Birr per hectare of irrigated land. Furthermore, the results showed a strong public preference for access to produce cash crops, followed by irrigation water availability in the dry season, and adequate access to improved farm inputs. The results also provide useful information for policymakers and suggested possibilities for generating finance from farmers to cover the operation and maintenance costs of irrigation schemes. Also, this study result reveals that irrigation development and expansion must be integrated into a comprehensive support package that combines irrigation water with access to improved farm inputs and access to produce cash crops on farmers' farm plots. [ABSTRACT FROM AUTHOR]

Abstract Single-vehicle crashes, particularly those caused by speeding, result in a disproportionately high number of fatalities and serious injuries compared to other types of crashes involving passenger vehicles. This study aims to identify factors that contribute to driver injury severity in single-vehicle crashes using machine learning models and advanced econometric models, namely mixed logit with heterogeneity in means and variances. National Crash data from the Crash Report Sampling System (CRSS) managed by the National Highway Traffic Safety Administration (NHTSA) between 2016 and 2018 were utilized for this study. XGBoost and Random Forest models were employed to identify the most influential variables using SHAP (Shapley Additive Explanations), while a mixed logit model was utilized to model driver injury severity accounting for unobserved heterogeneity in the data collection process. The results revealed a complex interplay of various factors that contribute to driver injury severity in single-vehicle crashes. These factors included driver characteristics such as demographics (male and female drivers, age below 26 years and between 35 and 45 years), driver actions (reckless driving, driving under the influence), restraint usage (lap-shoulder belt usage and unbelted), roadway and traffic characteristics (non-interstate highways, undivided and divided roadways with positive barriers, curved roadways), environmental conditions (clear and daylight conditions), vehicle characteristics (motorcycles, displacement volumes up to 2500 cc and 5,000–10,000 cc, newer vehicles, Chevy and Ford vehicles), crash characteristics (rollover, run-off-road incidents, collisions with trees), temporal characteristics (midnight to 6 AM, 10 AM to 4 PM, 4th quarter of the analysis period: October to December, and the analysis year of 2017). The findings emphasize the significance of driving behavior and roadway design to speeding behavior. These aspects should be given high priority for driver training as well as the design and maintenance of roadways by relevant agencies.

The popularisation of autonomous vehicles will give rise to a new business model called shared autonomous vehicle (SAV). SAVs may attract a large number of passengers and lead to a decline in the share of buses, which can be interpreted by exploring passengers’ travel behaviour when confronting the SAV and bus modes. Thus, this paper addresses the SAV and bus passengers’ travel behaviour, aiming to examine the factors influencing travel behaviour and revealing the characteristics of SAV passengers. We classified passengers using latent class cluster analysis and modelled passengers’ travel behaviour based on confirmatory factor analysis and mixed logit model. The findings indicate a variation in travel preferences among different classes of travellers. Short-distance travellers pay less attention to travel time. Non-short-distance PT travellers are most likely to be affected by service attributes (waiting time, travel time and travel costs). Non-short-distance private car travellers are more likely to become early SAV adopters. Passengers travelling for short distances may be more likely to choose SAV, which reveals the potential of SAVs to become a first and last mile connection for public transport. Passengers lack trust in SAVs, which will affect their promotion.

Single-vehicle crashes, particularly those caused by speeding, result in a disproportionately high number of fatalities and serious injuries compared to other types of crashes involving passenger vehicles. This study aims to identify factors that contribute to driver injury severity in single-vehicle crashes using machine learning models and advanced econometric models, namely mixed logit with heterogeneity in means and variances. National Crash data from the Crash Report Sampling System (CRSS) managed by the National Highway Traffic Safety Administration (NHTSA) between 2016 and 2018 were utilized for this study. XGBoost and Random Forest models were employed to identify the most influential variables using SHAP (Shapley Additive Explanations), while a mixed logit model was utilized to model driver injury severity accounting for unobserved heterogeneity in the data collection process. The results revealed a complex interplay of various factors that contribute to driver injury severity in single-vehicle crashes. These factors included driver characteristics such as demographics (male and female drivers, age below 26 years and between 35 and 45 years), driver actions (reckless driving, driving under the influence), restraint usage (lap-shoulder belt usage and unbelted), roadway and traffic characteristics (non-interstate highways, undivided and divided roadways with positive barriers, curved roadways), environmental conditions (clear and daylight conditions), vehicle characteristics (motorcycles, displacement volumes up to 2500 cc and 5,000–10,000 cc, newer vehicles, Chevy and Ford vehicles), crash characteristics (rollover, run-off-road incidents, collisions with trees), temporal characteristics (midnight to 6 AM, 10 AM to 4 PM, 4th quarter of the analysis period: October to December, and the analysis year of 2017). The findings emphasize the significance of driving behavior and roadway design to speeding behavior. These aspects should be given high priority for driver training as well as the design and maintenance of roadways by relevant agencies. [ABSTRACT FROM AUTHOR]

AbstractSince the launch of ChatGPT in November 2022, the number of services providing generative AI has been steadily increasing. As different services enter the market, the generative AI interfaces users experience become more diverse. However, none of the services has yet established itself as the dominant tool, and which interface component affects user preferences the most has yet to be identified. This study investigates user preferences based on the interface of generative AI services currently on the market. We investigated users’ preferred interface components by setting the output data type, generative style, output variation, reference style, and generation history provided by the current generative AI service as properties. We collected data from 500 users through a survey and conducted conjoint analysis. Users preferred the provision of 10 generation histories the most, and the second most preferred the provision of reference style in footnote format. In addition, it was found that there was no preference for the creative generative style, which can be interpreted as users being aware of the problem of hallucination in generative AI. The results of this study will help future generative AI services design interfaces that consider user experience. [ABSTRACT FROM AUTHOR]

There has been a concerning rise in pedestrian fatalities resulting from traffic accidents. This study conducts an in-depth analysis of the factors that contribute to the injury severity of pedestrians considering human, vehicle, roadway, and environmental characteristics of the crashes. A novel approach is proposed by combing a data mining technique and mixed logit models. First, the Apriori algorithm is employed to uncover patterns between fatal and incapacitating injury outcomes and their influencing factors. Then, mixed logit models are developed to investigate heterogeneity across all observations under two different lighting conditions. It is found that eight variables show heterogeneity affecting the injury severity of crash outcomes. Results also indicate that drivers older than 65 years old will increase the probability of pedestrian injury severity at dark-unlighted roads. Additionally, the present of signal and double yellow line has could increase the injury severity. Creating optimal lighting conditions at pedestrian crossings during nighttime hours and enhancing safety education initiatives for pedestrians are critical factors to improve pedestrian safety. The finding of this study will benefit policymakers and road safety professionals develop more effective strategies for preventing pedestrian injuries in vehicle crashes. [ABSTRACT FROM AUTHOR]

This paper presents a systematic investigation of the train choice preference heterogeneity of High-Speed Railway (HSR) passengers under market segmentation to understand their train choice comprehensively. A stated preference survey was conducted for the Nanning-Guangzhou Railway and Nanning-Beihai Railway. Latent Class Analysis (LCA) was employed to identify homogeneous subgroups and segment the passenger market of each line into three segments: private travelers with a long total duration (PTLTD), business travelers (BT), and private travelers with a short total duration (PTSTD). Mixed Logit (ML) models were constructed for each subgroup sample to assess passengers' preferences in train choice. The results show that each class exhibited unique characteristics and preferences, and train fare and running time, departure date and time, and train frequency were statistically significant factors affecting train choice. This study can furnish theoretical and decisional support for HSR operators to design train operating schemes and flexible fare systems. [ABSTRACT FROM AUTHOR]

A work-zone introduces unexpected conditions for road users and may cause severe safety issues. This study aims to understand drivers' pre-crash improper actions, which are the major contributing factor to the crash occurrence and outcomes severity in single-vehicle (SV) work-zone crashes. A mixed logit model with heterogeneity in mean and variance was developed using Florida's seven-year work-zone crash data. The estimated models investigated five pre-crash improper actions (no contributing action, careless driving, speeding, swerving lanes, and other pre-crash actions) in SV work-zone crashes. Year-paired likelihood ratio tests identified temporal instability existing in the dataset over the study period and suggested yearly model estimation to capture the temporal instability. The model results identified a wide range of variables that impact drivers' pre-crash improper actions, such as driver and weather conditions, work-zone type, and temporal and lighting characteristics. The findings of this study imply that driving psychology plays a critical role in safety-related driving behaviors in work-zone areas. Engineering or education countermeasures that could increase driver alertness of potential hazards are suggested to reduce improper actions by drivers and improve work-zone safety. [ABSTRACT FROM AUTHOR]

Two-vehicle crashes resulting from distracted driving led to a higher number of fatalities and serious injuries over time. This study utilized machine learning and econometric models to investigate two-vehicle-involved distracted driving crashes from the Crash Report Sampling System within the United States. XGBoost and Random Forest were utilized to identify the top variables based on SHAP value, although mixed logit with unobserved heterogeneity was used to model injury severity. The model results indicate that there is a complex interaction of driver characteristics, such as demographics (male drivers), driver actions (careless driving, driving more than the speed limit of more than 15 mph, hitting a stopped vehicle), a driver without violation history, turning violation, drinking, roadway characteristics (non-interstate highways, undivided and divided roadways with positive barrier, curved roadways, dry surface), environmental conditions (rainy weather), vehicle attributes (motorcycle, displacement volume up to 2500 cc, newer vehicle within five years of crash-involvement), temporal characteristics (4–6 PM, July–September, and year 2017). These findings underscore the importance of driving behavior and roadway design. As such, prioritizing efforts to address distracted driving behavior through driver training and law enforcement, as well as considering its implications for roadway design and maintenance, becomes crucial. [ABSTRACT FROM AUTHOR]

The objective of this research is to explore the determinants of shared bike route choice in both urban and rural settings in Germany. To this end, a stated preference (SP) survey on route choice was conducted across several German cities. Participants were drawn from the service area of a regional bike-sharing system (BSS) in Germany. This area included five major cities and several mid-sized and smaller municipalities. The survey includes responses from both users and non-users of the BSS. Mixed multinomial logit models were used in analysis of the SP data. The study also calculated the willingness to pay (WTP) values for selected attributes. Significant influences on route choice included access and egress time, ride time, and ride cost. Significant random heterogeneity was found, especially for ride cost. Further heterogeneity was reported for interactions with sociodemographic attributes. Street type, surface, and bike infrastructure also had significant effects on route choice. Linkages between infrastructural preferences and respondents’ ages were evident. Although WTP values were strongly influenced by random heterogeneity in ride cost perception, most WTP values were comparable to the values obtained in other studies.

Pedestrian safety has always been a concern at urban intersections, especially in low-income developing countries with higher casualty rates. As one of the cities with the highest pedestrian fatality rates in Iran, Mashhad lacks studies that pinpoint the causes of these crashes. The choice of appropriate methodology was guided by the two-fold objective of the study: first, disaggregating crashes into homogeneous clusters; and second, examining the effects of risk factors on pedestrian crashes while accounting for the inherent unobserved heterogeneity in crash data. The study compared the classification accuracy of modeling approaches using receiver operating characteristic analysis. By analyzing three years (2015–2017) of pedestrian crashes in Mashhad, this study identified risk factors associated with higher severity of vehicle–pedestrian crashes at intersections. The results show that models incorporating the heterogeneity effect, such as the cluster-aggregated model and the random parameter model, have higher classification accuracy for crashes than models that do not consider heterogeneity. Based on the risk factors associated with increasing fatal crashes, several low-budget and immediate countermeasures are suggested in the hope of improving pedestrian safety at intersections.

The present study aims at investigating the main and interaction effects of contributing factors from multiple risk sources (i.e. traffic flow characteristics, roadway design and weather conditions) on the real-time crash risk for urban roads. A mixed logit model is used to characterise heterogeneity induced by unobservable factors, and result shows that the mixed logit model achieves better goodness-of-fit than the binary logit model. It is found that the multiple risk sources such as roadway design (i.e. length of road segment, road hierarchy), traffic flow characteristics (i.e. average speed, average travel time, congestion level), and weather conditions (i.e. wind speed) have significant effects on the real-time crash risk. Moreover, interactions between the multiple risk sources such as roadway design and traffic flow characteristics (i.e. SD of speed and length of road segment, road hierarchy and average travel time), traffic flow characteristics and weather conditions (i.e. average travel time, temperature and wind speed), and roadway design and weather conditions (i.e. length of road segment and wind speed) are found to be significantly correlated to the real-time crash risk. Such findings can be potentially used for the development of real-time management measures that could mitigate the high-risk situations of urban roads. [ABSTRACT FROM AUTHOR]

Existing studies have not analyzed travelers' travel modal shift behavior after bus fare adjustment for special urban topography. In order to fill this gap and explore the strategies that can effectively encourage the shift of valley city travelers to rail transit after the adjustment of bus fare, the price adjustment perception and topographic space perception are introduced to expand the theory of planned behavior (TPB). On this basis, an integrated model combining structural equation model (SEM) and Mixed Logit model (MLM) is established to analyze the factors of travelers’ modal shift behavior of in the valley city after bus fare adjustment, and elastic analysis is carried out. Taking Lanzhou as an example, questionnaire data and traffic data were collected for example analysis. The results show that fare adjustment perception (FAP) and topographic space perception (TSP) have the same significant impact on travel modal shift intention (TMSI) and behavior (TMSB) as subjective norms (SN), shift behavior attitude (SBA) and perceived behavior control (PBC), and the travel characteristics and psychological perception sensitivity of travelers in the valley city are heterogeneous. After the adjustment of bus fares in valley city, the shift to rail transit is the most. When the subjective norms, fare adjustment perception and topographic space perception of travelers in the valley city increase by 50 %. The sharing rate of rail transit is increased by 10.284 %. The effective way to increase the sharing rate of rail transit is to increase the combined factors of subjective norms, topographic space perception and fare adjustment perception. Compared with the Multinomial Logit model and the Logit model combined with structural equation model, the goodness of fit and prediction accuracy of the proposed integrated model are improved.

The effect of vehicle transmission type on driver injury severities have not been thoroughly studied. The study used four-year historical crash data that occurred between the year 2019 and 2022 in Ghana. The data shows 1856 and 2272 crashes for automatic and manual transmission, respectively. The study examined the factors influencing driver injury severity in crashes involving vehicles with manual and automatic transmissions, using Random Parameter Mixed Logit Model to account for heterogeneity in the dataset. It was observed that use of manual transmission is related to a higher risk of incapacitating and fatal injuries compared to automatic transmission. Specifically, for automatic transmission vehicle-involved crashes, factors related to fatal injury were overaged vehicles, public transport, morning and evening peak hours, head-on and rollover crashes. Crashes involving saloon cars and low age cars were associated with incapacitating injury whiles rainy weather condition was related to both fatal and incapacitant injuries. Regarding manual transmission, fatal injury was associated with crashes involving male and novice drivers, cars, pickup trucks, HGV, public transports, morning and evening peak hours, rainy weather conditions and curved roads. Also, buses, private cars and trip distance were related to incapacitating injury. The rollover crashes and overaged vehicles were also associated with both fatal and incapacitating injuries. Four random parameters demonstrated heterogeneity in means, with two factors influencing the variances of two parameters for automatic transmission model. For the manual transmission model, five random parameters showed heterogeneity in means, with four variables influencing the variances of three parameters. These findings are valuable for policymakers, manufacturers, and drivers in implementing targeted interventions and safety measures to promote road safety.

This study estimates the influence of the coronavirus disease 2019 (COVID-19) pandemic on consumer preferences for turfgrass attributes by analyzing data from two surveys conducted in Jan 2019 and Apr 2021. First, the study estimated a mixed logit model to account for individual heterogeneity in preferences. Subsequently, estimates of the willingness to pay (WTP) were compared between periods before and after the pandemic. To show the impact of consumers' risk attitudes with respect to climate change on their preference for turfgrass attributes, we re-estimated the model according to the risk attitude groups (i.e., risk-seeking vs. risk-averse). Finally, to examine how consumers' demographic characteristics and risk attitudes are related to their WTP for improved turfgrass attributes, we estimated a random-effect panel data model for each attribute. Our results showed that, overall, consumers' WTP increased during the COVID-19 pandemic. We also found that the WTP of risk-averse consumers were mostly higher than those of risk-seeking consumers during both time periods. Furthermore, the increase in the WTP observed among the risk-averse group was greater than the increase of the WTP of the risk-seeking group. Our findings imply that the demand for drought-tolerant and stressresistant turfgrasses would increase with possible future climate changes and infectious disease outbreaks. [ABSTRACT FROM AUTHOR]

Based on the Mixed Logit model, the willingness-to-pay (WTP) for waste mobile phone recycling among college students in Beijing was investigated using a discrete choice experiment method. The research results three aspects of respondents' choices and WTP. (1) Their choices are positively affected by information security, recycling price, recycling method and payment method, and negatively affected by payment amount. (2) Respondents have the highest WTP for information security (30.04 yuan), followed by the recycling price (5.94 yuan) and payment method (4.41 yuan), and the lowest WTP for recycling models (2.87 yuan). (3) Personal socio-economic characteristics such as gender, annual household income, and the number of mobile phones held by respondents have significant impacts on their recycling WTP. The deeper the respondents' awareness of the environmental protection effect of waste mobile phone recycling, the more enthusiasm they have for the recycling behavior, the higher their participation in recycling, and the higher their WTP for recycling. [ABSTRACT FROM AUTHOR]

• The severity of single-vehicle truck crashes was investigated. • Separate models for each crash type were estimated. • Mixed logit was employed to account for unobserved heterogeneity. • Influential factors were explored and discussed. • Safety countermeasures were proposed. Introduction: Almost 90% of fatal road crashes occur in developing countries. Among these countries, Iran has a noticeable fatal crash rate of 21.47 deaths per 100,000 persons. Improving the safety of trucks is of particular importance in Iran where road freight is used to transport almost 90% of the commodities. Researchers have suggested dichotomizing crashes into single- and multi-vehicle categories and found that when this is performed vast differences can be identified between the mechanisms behind these categories of crashes, particularly when investigating truck crashes. Method: This study investigated single-vehicle truck crashes in Khorasan Razavi province in Iran from 2013 to 2021. Likelihood ratio tests were employed to show that separate models are statistically valid for different crash types. Subsequently, three mixed logit crash-type models were developed to investigate 5,703 single-vehicle truck crashes. Results: Four significant variables were exclusive to collisions with an object (brake failure, ABS, primary roads, and rainy or snowy weather), five significant variables were associated with run-off-road crashes (driving a loaded truck, speed limit (> 60 km/h), paved shoulders, driving uphill, and inability to control the truck), and three significant variables were associated with overturn crashes (overloaded truck, curved roads, and changing direction suddenly). In all crash types, both fastening the seatbelt and speeding were found to be significant factors. Conclusion : The research highlights the need to analyze single-vehicle truck crashes using distinct crash type models and highlights the unique contributing factors of three common single-vehicle crash types. Practical applications : The study presents recommendations for policy to address key crash risks for trucks in Iran, including education and training to improve driver experience, compliance with seat belt usage, enforcement of speeding, and vehicle technologies to monitor drivers. [ABSTRACT FROM AUTHOR]

Designing incentives for agri-environmental public good provision with threshold effects calls for payment mechanisms favouring critical mass participation and continuity of commitments at the landscape scale. We conducted a choice experiment to test the acceptability of a bonus in a scheme for improving river water quality in France. We introduce a sponsorship bonus each time the farmer convinces a peer into entering the scheme, which can be combined with a collective result bonus per hectare if the river reaches a higher step on the water quality scale. We consider the involvement of local financers could increase the willingness to pay beyond opportunity costs and income foregone and propose higher levels of payment than agri-environmental schemes. Results suggest a sponsorship bonus on its own is cost-effective. We characterize respondents’ heterogeneity and identify three groups based on choice patterns: (i) “pro-environment individualists”, (ii) “management change averse” farmers, and (iii) “pro-incentive” farmers. [ABSTRACT FROM AUTHOR]

To reduce greenhouse gas (GHG) emissions and achieve carbon neutrality, worldwide governments are establishing various policies and systems for the diffusion of renewable energy. Hydrogen fuel cell (HFC) is evaluated as a next-generation energy source as it can supplement the existing renewable energy sources, while providing stable energy supply and demand. To address low HFC generation share, the Korean government introduced the world's first Hydrogen Portfolio Standard (HPS) into the energy market, where public acceptance is crucial for the implementation of such policies. Thus, this study analyzed the public preference and acceptance for HPS through a discrete choice experiment. Although the public accepted the HPS itself, they preferred a higher proportion of fuel cell generation when the fuel cell was operated through clean hydrogen (blue/green hydrogen). Specifically, the marginal willingness to pay values for a 10% increase in fuel cell generation when changing from grey hydrogen to blue hydrogen or green hydrogen were estimated to be USD 1.94 and 2.97, respectively. Further, the acceptance of green hydrogen-based HPS rises along with the expansion in the HFC generation share. Thus, to expand the fuel cell generation in the national energy mix, transition to a clean hydrogen-based energy system should be attached. • Public's inclination toward hydrogen fuel cells (HFCs) technology was analyzed. • Discrete choice experiment analyzed public inclination toward alternatives. • Marginal willingness to pay (MWTP) and relative importance (RI) were analyzed. • Electricity rates have a significant impact on energy system acceptability. • Public acceptance of fuel cell power increased when clean hydrogen was used. [ABSTRACT FROM AUTHOR]

Shipping lines avoid tax burdens and policy requirements by registering their self-owned vessels in flag of convenience (FOC) countries and establishing subsidiaries in those countries. However, since the international tax system has been increasingly focused on substance, coherence, and transparency, the anti-tax avoidance rules may have affected the choice of registry for shipping lines. Based on the 900-ship registry data of the top 25 liners across 26 flag states over the period 2008 to 2019, this paper uses conditional logit and mixed logit models to examine the effect of anti-tax avoidance rules on the choice of registry for shipping lines. In this regard, the results indicate that introducing country-by-country reporting requirements and a common reporting standard will reduce the probability of shipping lines registering to flag in those countries. On the other hand, after imposing anti-tax avoidance rules, liners are more willing to register flags in countries with higher tax rates. The results of a regional analysis show that better tax performance exerts an adverse effect on flag choice of European shipping lines; however, it has the opposite effect on Asian shipping lines. [ABSTRACT FROM AUTHOR]

Plant-based meat could contribute substantially to nutritional security and environmental sustainability. Nevertheless, its diffusion is highly dependent on consumers’ perception and acceptance. Plant-based meat products have various attributes through which nutritional, environmental, and ingredient information are delivered to consumers. To elucidate consumers’ preferences for these attributes, we conducted a large-scale consumer survey in five major cities of the largest national meat consumption market, China, with a total of about 2500 respondents. Best-worst count analysis indicated that “zero cholesterol” is the most preferred and “vegan formula” is the least preferred attribute. Mixed logit model analysis showed that “rich in dietary fiber”, “zero hormones”, and “zero cholesterol” are the three most preferred attributes. Latent class model analysis revealed that respondents with better socioeconomic conditions tended to focus more on the positive nutritional aspects of plant-based meat, whereas respondents with worse conditions tended to place a higher value on avoiding negative health impacts of traditional meat when choosing plant-based meat. This study suggests that Chinese consumers pay more attention to nutritional attributes as compared to other attributes. In addition, apparent market segments exist among different consumers. The findings of this study could contribute to the transformation of sustainable food system.

Wrong Way Driving (WWD) by motorcycle riders is a traffic violation that may cause crashes. It is frequently encountered in developing countries. The purpose of this study is to examine the factors influencing WWD among motorcycle riders. This study selected six sites in Khon Kaen city, Thailand, to examine motorcycle riders’ driving behavior, either WWD or law-obeying driving, such as when making a U-turn. The driving behaviors of 1,114 motorcycle riders were collected. The random parameter mixed logit model was applied to analyze the correlation between motorcycle riders’ WWD behavior and influencing variables. The results indicated that WWD influencing factors included gender, helmet wearing, time of day, motorcycle size, the presence of LED warning signs, control of U-turn median opening, and the ratio of the travel distances between the law-obeying route and the WWD route. Finally, this study proposed recommendations to reduce the occurrence of motorcycle riders’ WWD behavior.

IntroductionFarmers are under increasing pressure to use fewer pesticides for production and pest control. Farmers and other producers are responding to consumer concerns about pesticides by creating new marketing opportunities for products grown with environmentally friendly practices. The purpose of this study is to estimate consumers' willingness to pay for each of the information provided in the "Protective Agriculture Label" and determine the factors affecting consumers' willingness to pay. The two conservation agriculture labels designed in this study are the "How to Cultivate" label and the "Environmental Damage" label. The cultivation method label provides information about the raw materials used to produce the product, while the environmental damage label provides information about the environmental harm caused during the production process. The purpose of this study is to estimate consumers' willingness to pay for each type of information provided on the conservation agriculture labels and to determine the factors affecting consumers' willingness to pay.Materials and Methods In this study, in order to analyze consumers' preferences for protective agricultural products in Mashhad, the choice experiment method was used, and conditional logit models and logit with random parameters were used to estimate its parameters. Choice experiment is a common tool for valuing environmental functions and services. The required information was obtained by completing 170 questionnaires from the consumers of Mashhad city. The analysis of collected data is done using many models, most of which have a logit form. In this study, conditional logit and logit models with random parameters have been used to investigate the effect of the characteristics of agricultural product labels on consumers' willingness to pay and to estimate the amount of willingness to pay for each of the characteristics. Results and DiscussionIn this article, consumer preferences for protective agricultural products have been analyzed using the choice test method. For data analysis, conditional logit and logit with random parameters model were used. The results obtained from this study have shown that the characteristic accuracy of the measurement method was the highest and the label-issuing organization had the lowest willingness to pay. The variables of gender, the presence of a child in the family, and the presence of people with a specific disease in the family had a positive and significant effect, and the variable of age had a negative and significant effect on the willingness of consumers to pay. In both labels, the sign of the price variable is negative, which is in accordance with the theory of economic utility. The comparison of the calculated final effect for two labels of environment and method of cultivation has shown that, in general, the probability of choosing the label of method of cultivation is higher than the probability of choosing the label of environmental-biological damages. In 53% of the cases, the selected option was the label of how to cultivate, and in 15% of the cases, none of the labels were selected. The amount of willingness of consumers to pay to obtain information about the way of cultivation and damage to the environment is very low. Even consumers willing to pay to obtain detailed information on production (such as the degree of water pollution with which the product was irrigated, the level of soil pollution in which the product was grown, and the type of poisons used) and environmental damage (such as contamination of groundwater with The reason for product production is not air pollution due to product production and global warming (increasing temperature due to product production). In this regard, more research is suggested in the field of reasons for the low willingness to pay of consumers.ConclusionExamining the willingness to pay of consumers has shown that people are willing to pay more for the accuracy of the measurement method than for the label-issuing organization. The amount of consumers' willingness to pay for the characteristics of the organization issuing the label and the accuracy of the measurement method were obtained as 5 and 17.04 Tomans, respectively, so it can be concluded that Accuracy is more important than an organization for consumers.

Bicycling has been actively promoted as a clean and efficient mode of commute. Besides, due to the personal and societal benefits it provides, it has been adopted by many city dwellers for short-distance trips. Despite the integral role this active transport mode plays, it is unfortunately associated with a high risk of fatalities in the event of a traffic crash as they are not protected. Many studies have been conducted in several jurisdictions to examine the factors contributing to crashes involving these vulnerable road users. In the case of Louisiana which is currently experiencing increased cases of severe and fatal bicycle-involved crashes, less attention has been paid to investigating the critical factors influencing bicyclist injury severity outcomes using more detailed data and advanced econometric modeling frameworks to help propose adequate policies to improve the safety of riders. Against this background, this study examined the key contributing factors influencing bicyclist injuries by using more detailed roadway crash data spanning 2010–2016 obtained from the state of Louisiana. The study then applies an advanced random parameter logit modeling with heterogeneity in means and variances to address the unobserved heterogeneity issue associated with traffic crash data. To overcome the imbalanced data issue, three major crash injury levels were used instead of the conventional five crash injury levels. Besides, the data groups classified under each injury level were compared for the final variable selection. The study found that distracted drivers, elderly bicyclists, careless operations, and riding in dark conditions increase the probability of having severe injuries in vehicle-bicyclist crashes. Moreover, the variables for straight-level roadways and city streets decrease the odds of severe injuries. The straight-level roadway may provide better sight distance for both drivers and bicyclists, and complex environments like city streets discourage crashes with severe injuries.

Recent surge in gasoline prices has impacted travel costs which in turn have influenced model choice by travelers. Anticipating the mode choice of the public has become important in strategically developing future transportation systems. Urban travelers were surveyed. Travel mode choice behavior of travelers in different situations were obtained. The travelers were divided into private vehicles owners and non-owners groups with be willing to buy a car in the next five years, and the mixed Logit model was used to construct the travel mode choice models of the two groups under the influence of gasoline price hike. The significance of each factor was analyzed. Results show that the hiking rate of gasoline prices has a significant impact on travelers' choice of travel modes. For the private vehicle owners group, the rise of gasoline price has little impact on high-income travelers' change of car travel, and income is positively correlated with the probability of choosing by car. Age, income, travel time and travel distance have a significant impact on nonowners travelers' choice of car travel in the future. The research conclusions can provide a theoretical basis for the adjustment of gasoline prices and the formulation of traffic demand management strategies in China. [ABSTRACT FROM AUTHOR]

Objective: The Italian healthcare jurisdiction promotes patient mobility, which is a major determinant of practice variation, thus being related to the equity of access to health services. We aimed to explore how travel times, waiting times, and other efficiency- and quality-related hospital attributes influenced the hospital choice of women needing pelvic organ prolapse (POP) surgery in Tuscany, Italy. Methods: We obtained the study population from Hospital Discharge Records. We duplicated individual observations (n = 2533) for the number of Tuscan hospitals that provided more than 30 POP interventions from 2017 to 2019 (n = 22) and merged them with the hospitals' list. We generated the dichotomous variable "hospital choice" assuming the value one when hospitals where patients underwent surgery coincided with one of the 22 hospitals. We performed mixed logit models to explore between-hospital patient choice, gradually adding the women's features as interactions. Results: Patient choice was influenced by travel more than waiting times. A general preference for hospitals delivering higher volumes of interventions emerged. Interaction analyses showed that poorly educated women were less likely to choose distant hospitals and hospitals providing greater volumes of interventions compared to their counterpart. Women with multiple comorbidities more frequently chose hospitals with shorter average length of stay. Conclusion: Travel times were the main determinants of hospital choice. Other quality- and efficiency-related hospital attributes influenced hospital choice as well. However, the effect depended on the socioeconomic and clinical background of women. Managers and policymakers should consider these findings to understand how women behave in choosing providers and thus mitigate equity gaps. [ABSTRACT FROM AUTHOR]

For health, environmental, and animal welfare reasons, an increase in the consumption of meat in our diet is of great concern in today's society. Meat substitutes have been advocated for a long time as a solution to these problems and are evolving continuously with technological advancements. Despite these efforts, it is remarkable that meat alternatives only account for a small portion of the global meat market. As a result, we examined the factors that affect Flemish consumers' preferences for meat substitutes in Belgium using a discrete choice experiment. We also examined consumers' preferences after providing additional information, as well as the impact of color-coding certain attribute levels on their preferences. The study was conducted using a sample size of 162 participants selected via convenience sampling. The findings show that it is important to keep the sensory properties of meat substitutes similar to those of actual meat. The results also indicate that additional information regarding the environmental and health impact of meat consumption can help to promote meat substitutes. The traffic light color coding of the levels of saturated fat and ecofootprint attributes increases the preference for healthy and environmentally friendly alternatives. Finally, we observed that individual-level variations in the utility attributed to meat substitutes are explained significantly by age, gender, education, current diet group, and attitudinal factors. Overall, we can conclude that the promotion of meat substitutes can be achieved via a combined strategy that focuses on improving the taste, appearance, and nutritional profile of meat substitutes, as well as raising consumers' awareness of the environmental and health impact of meat consumption. [ABSTRACT FROM AUTHOR]

The transportation sector in India faces significant issues, such as congestion and air pollution, and is in dire need of sustainable strategies. Sharing vehicles is one of the popular sustainable strategies. Sharing auto-rickshaws, a paratransit mode, currently informally operating with a significant mode share, offers an opportunity to tackle sustainability issues. There are several challenges to integrating and promoting auto-rickshaw system as shared transportation using a formal structure of policies. The primary reason is a dearth of studies on sharing auto-rickshaws, leading to policymakers lacking knowledge and focus. The present study contributes to the literature to divert focus on sharing auto-rickshaws in India, considering Mumbai Metropolitan Region (MMR) as a study area. This study attempts to assess and model the intentions of users and non-users toward auto-rickshaw sharing using stated preference (SP) choice experiments and estimate Willingness-to-Pay (WTP) considering multiple socio-economic heterogeneities. Results highlight that the most critical attributes are travel time reliability and access time among different groups. Importance of having real-time information on trips among females and sharing auto-rickshaw users is high. The study provides a transparent direction toward ensuring efficient and integrated policymaking and guidelines for promoting auto-rickshaw sharing in urban areas of the Indian subcontinent with limited resources. • Perception of users and non-users of sharing auto-rickshaws are compared. • Segmentation analysis is used to assess heterogeneity among different subgroups. • Willingness to pay for the subgroups is estimated by Mixed-logit modeling. • Travel time reliability and Access time are most important for all sub-groups. • Clear direction to promote auto-rickshaw sharing and integrate it into policymaking. [ABSTRACT FROM AUTHOR]

This paper presents the findings of an activity-based tour-level model that jointly investigates individuals' decisions of activity-tour participation, time allocation, and mode choice. A multiple discrete continuous extreme value (MDCEV) model is developed that explores the participation and time allocation decisions for mandatory, maintenance, and discretionary activity-tour types. Mixed logit (MXL) models are developed to evaluate the mode choice decisions of individuals for different activity-based tours. Logsum values, which represent the modal accessibility, are introduced within the MDCEV modeling framework as feedback mechanisms from mixed logit models that exclusively examine the influence of individuals' mode choice on their activity-tour engagement decisions as well as ensure the integrity of the decision modeling system. Findings of this study would assist the policymakers to develop effective strategies for better transportation investment decisions. [ABSTRACT FROM AUTHOR]

Roundabout crashes are common worldwide but have received little attention. In particular, the investigation remains relatively understudied in distinct collision modes of roundabout crashes, including angle and non-angle crashes. This study investigates differences in factors affecting injury severity between angle and non-angle crashes and how these differences change over time. Random parameter logit models with heterogeneity in mean and variance were estimated using 2012–2019 Florida crash data. Variables considered for the modeling include temporal characteristics, environmental characteristics, road characteristics, spatial characteristics, vehicle characteristics, crash characteristics, and human characteristics. In addition, likelihood ratio tests were used to investigate the temporal instabilities of the models and differences in collision modes. The results showed that only a few variables demonstrated temporally stable effects for angle collisions (weekend and dark-lighted) and non-angle collisions (paved shoulders and cyclists), respectively. Unique influencing factors of injury severity were identified for different collision modes, such as dark-lighted, straight alignment, merge, lane departure, the disabled driver for angle collisions, and clear, fog, commercial vehicles, and aggressive driving for non-angle collisions. The results of the out-of-sample prediction simulations further demonstrate the difference in injury severity over time for angle and non-angle collisions. Overall results suggest that countermeasures can be implemented to reduce the injury severity of angle crashes/non-angle crashes based on the significant variables identified. This study may be used to improve roundabout safety by considering different collision modes. [ABSTRACT FROM AUTHOR]

Similar to many countries, China has introduced a variety of incentives to promote the use of energy-efficient appliances. The Chinese government introduced the energy-efficiency labeling program in 2005, and three types of subsidies (i.e., the countryside subsidy, trade-in subsidy, and eco-product subsidy programs) were implemented from 2007 to 2013. In this study, we examine households’ selection of refrigerator energy efficiency and apply a mixed logit model to micro-level data from the Chinese General Social Survey to evaluate the impact of these policies. The analysis demonstrates that the energy-efficiency labeling program as well as the three subsidy programs promoted households’ choice of energy-efficient refrigerators; however, the effects of the various subsidy programs differed. These results suggest that the countryside subsidy has a similar effect as the eco-product subsidy in terms of promoting the purchase of highly energy-efficient refrigerators, although the countryside subsidy’s main objective was to promote appliances being disseminated in rural areas. The trade-in subsidy was less effective in promoting the sale of energy-efficient refrigerators. These findings provide implications for designing future incentive and subsidy policies, particularly for developing countries. [ABSTRACT FROM AUTHOR]

We investigate US consumers' willingness to pay for cotton apparel production and country of origin attributes. Using a choice‐based conjoint experiment and information treatments, we examine the preferences of 727 US shoppers for the attributes: cotton fiber production systems and country of manufacture of the cotton fiber. Random utility theory is the basis for the survey's responses analysis to estimate willingness to pay (WTP) values for the attributes. Choices made by consumers are modeled using a mixed logit model in WTP space estimated using simulated maximum likelihood procedures. Results show that consumers are willing to pay more for cotton apparel from the United States than apparel from other countries, and more for apparel made from fiber produced in organic systems than in conventional systems. Only some subgroups of consumers were found to be affected by exposure to an information treatment regarding potential labor exploitation in cotton farms and textile mills. [EconLit Citations: D12]. [ABSTRACT FROM AUTHOR]

The effect of sealed or unsealed road pavements on motorist’s injury severities has not been extensively explored. This study collected a four-year crash dataset (2015–2018) from South Australia to explore this issue. The data shows 3,812 and 1,086 crashes at sealed and unsealed pavement surfaces, respectively, during those years. This study examines the consequence of sealed and unsealed pavements on driver injury severity outcomes of motor vehicle crashes. A mixed logit model was developed by accounting for heterogeneity in means and variances of the random parameters. The variables were distributed among several categories: driver, temporal, spatial, roadway characteristics, crash type, vehicle type, and vehicle movement. Four random parameters were observed in the sealed model, whereas five parameters were in the unsealed one. Moreover, the sealed pavements model showed substantial heterogeneity in means of four of the random parameters, while the unsealed pavements model has some heterogeneity in both means and variances of some of the random parameters. Marginal effect results indicate that two indicator variables have enlarged the likelihood of driver severe injury consequences in sealed, alcohol involvement and posted speed limit > 100 km/hr. Additionally, four other significant variables sustain the probability of severe injury outcomes at unsealed pavement like male drivers, middle-aged drivers, rollover crash types, and crashes at straight roads. Based on these variables, various countermeasures were recommended to enhance the safety of both types of pavements.

Ridesharing transportation services as the leading transport systems in recent years have already invested in shared autonomous vehicles (SAVs) as the next generation of shared transportation systems. Recent years have seen a noticeably accelerating rate in utilizing advanced communications and mapping service technologies that opened new doors to the ridesharing operators to provide a better quality of service to the users; therefore, it is necessary to have a better insight in-to the preferences of the users for using SAVs. This study aims to identify individuals' preferences for using SAVs and investigate related demographic characteristics and travel behavior attributes. An online Adaptive Choice-Based Conjoint (ACBC) survey will be designed and implemented between March to May 2020 in the United States. Then a series of mixed logit models (MXLs) were used to estimate participants' preferences. The results show that females are more tended to use door-to-door services, younger riders are more interested in using SAVs and also accept longer travel times, and riders with high-income levels are willing to use SAVs with higher equipment and convenience door-to-door service and not share their trips with others. Furthermore, more educated riders are more likely to use door-to-door service, select a service with shorter travel time, and pay a little more money to insure their trip against possible delays. [ABSTRACT FROM AUTHOR]

Background: In the treatment of Non-Small Cell Lung Cancer (NSCLC) the combination of Immuno- Oncotherapy (IO) and chemotherapy (CT) has been found to be superior to IO or CT alone for patients' survival. Patients and clinicians are confronted with a preference sensitive choice between a more aggressive treatment with a greater negative effect on quality of life versus alternatives that are less effective but have fewer side effects. Objectives: The aims of this study were to: (a) quantify patients' preferences for relevant attributes related to Immuno-Oncotherapy treatment alternatives, and (b) evaluate the maximum acceptable risk (MAR)/Minimum acceptable benefit (MAB) that patients would accept for treatment alternatives. Methods: An online preference survey using discrete-choice experiment (DCE) was completed by NSCLC patients from two hospitals in Italy and Belgium. The survey asked patients' preferences for five patient- relevant treatment attributes. The DCE was developed using a Bayesian D-efficient design. DCE analyses were performed using mixed logit models. Information regarding patient demographics, health literacy, locus of control, and quality of life was also collected. Results: 307 patients (158 Italian, 149 Belgian), stage I to IV, completed the survey. Patients preferred treatments with a higher 5-year survival chance as the most important attribute over all the other attributes. Preference heterogeneity for the attribute weights depended on health literacy, patients' age and locus of control. Patients were willing to accept a substantially increased risks of developing side effects in exchange for the slightest increase (1%) in the chance of surviving at least 5 years from the diagnosis of cancer. Similarly, patients were willing to accept a switch in the mode of administration or complete loss of hair to obtain an increase in survival. Conclusion: In this study, the proportion of respondents who systematically preferred survival over all other treatment attributes was particularly high. Age, objective health literacy and locus of control accounted for heterogeneity in patients' preferences. Evidence on how NSCLC patients trade between survival and other NSCLC attributes can support regulators and other stakeholders on assessing clinical trial evidence and protocols, based on patients' conditions and socio-demographic parameters. [ABSTRACT FROM AUTHOR]

This study evaluates people's environmental preferences for future development scenarios, investigates the heterogeneity of their preferences, and discusses the potential conflicts using four hypothetical future development scenarios, namely the natural capital-based and compact society (NC), the natural capital-based and dispersed society (ND), the produced capital-based and compact society (PC), and the produced capital-based and dispersed society (PD). The choice of future development scenarios is an essential issue because it can alter development pathways and change the quality and quantity of natural capital in the future. However, it is still unclear what preferences people express for multiple future development scenarios. Identifying people's preferences for future development scenarios can help identify potential conflicts in decision-making and facilitate consensus building. This study conducts a discrete choice experiment employing participants from Ishikawa Prefecture (Japan). The mixed logit and latent class logit models reveal the preference heterogeneity of the inhabitants. Additionally, using the spatial Kriging method predicts the spatial distribution of people's environmental preferences, and the following are the findings: (1) participants generally prefer the ND scenario, although they exhibit heterogeneous preferences; (2) some groups of participants only have strongly preferred scenarios, while others have undesirable ones; (3) one group hesitates to pay additional taxes, while others are unresponsive; and (4) spatial heterogeneity in environmental preferences is suggested. Based on these results, the potential conflicts that may arise from future land-use policies and the policy implications are proposed. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate people's preferences for the geographical distance between residential locales and two types of urban agricultural land, namely, traditional agricultural land and a more complex and intensive agricultural landscape called "satoyama" and to evaluate the heterogeneity in people's preferences. The enhancement of urban sustainability is a crucial issue in sustainable development that can be potentially improved by urban agriculture. However, urban residents' perceptions and preferences regarding the distance between urban agricultural land and their locales remain unclear, and concrete measures to maintain and expand urban agriculture are still vague. Therefore, an online survey and choice experiment was conducted, with respondents from Ishikawa Prefecture in Japan, who are assumed to be familiar with the agricultural context. Mixed logit and latent class logit models were employed to evaluate urban residents' heterogeneous perceptions and preferences. The results reveal that: (1) urban residents generally prefer urban agricultural land in areas away from their residence; (2) preferences are diverse, and those who are relatively young, with higher income, and more environmentally conscious favor dwelling near urban agricultural land; (3) there is a quadratic relationship between the distance connecting people's locales and urban agricultural land, and thus, the most desirable distance exists; and (4) there is a difference in the proximity that people prefer between traditional agricultural land and satoyama. Based on the results, policy implications for urban planners and policymakers include implementing urban agriculture in peri-urban areas and handling a tradeoff between residential opposition and the intensity of urban agriculture. [ABSTRACT FROM AUTHOR]

This study investigates the effectiveness of sustainability labels, environmental attitudes, food safety concerns, and knowledge on Vietnamese consumer preferences for sustainably farmed shrimp. Mixed logit and latent class models were applied to estimate utility functions based on 459 samples collected using a choice experiment. The results indicate that Vietnamese consumers prefer sustainably farmed shrimp to conventionally farmed shrimp. Also, both food safety concerns and consumer knowledge vigorously promote sustainably farmed shrimp choices. Notably, the latent class results show that 73.5% of the respondents consider their environmental concerns about shrimp production when making decisions about consumption. The results indicate that placing information related to eco-friendly and food safety attributes on sustainability labels provides Vietnamese consumers with additional choices in the form of sustainably farmed shrimp. Finally, the simulated MXL results in the WTP space are more significant than those in the preference space, indicating that it is necessary to estimate the MXL in the WTP space to avoid specifying the parameter distribution subjectively by analysts. [ABSTRACT FROM AUTHOR]

The entrances of tunnels are generally considered to be accident-prone locations, and accidents related to this area mainly include rear-end and sideswipe crashes, which are also associated with lane-changing behaviours. Despite the extensive literature on the safety of lane-changing, little attention has been given to lane-changing behaviours in front of the tunnel entrance. To this end, this study investigates the contributing factors to the potential risk status of lane-changing, taking into account lane-changing scenarios and the distance to tunnel entrances. Vehicular trajectory data on adjacent sections of tunnel entrances was collected by naturalistic driving tests, and 615 lane-changing scenarios were extracted for analysis. Furthermore, lane-changing risk margin (LCRM) is proposed to estimate whether there is at potential risk during lane-changing. To verify the influence of risk factors on the safety of lane-changing on adjacent sections of tunnel entrances, a mixed logit model is established for different lane-changing scenarios and distance levels to tunnel entrances. The model estimation results indicate that the leading vehicles in the current lane and target lane (defined as CLV and TLV, respectively) significantly affect the risk of lane-changing, with the presence of CLV increasing the probability of performing risky lane-changing as approaching the tunnel entrance, while the presence of TLV instead reduces the probability of performing risky lane-changing behaviour. The distance to the tunnel entrance also has a significant impact on the risk of lane-changing, and the probability of the risk of lane-changing is higher at relatively close distances than at relatively long distances. Moreover, on adjacent sections of tunnel entrances, drivers mainly change lanes to the left, which is likely to be related to safer driving on the left. This implies that drivers approaching the tunnel may try to achieve better driving conditions before entering the tunnel by changing lanes in view of the complex driving conditions inside the tunnel.

Cycling provides an important alternative to environmental-friendly transportation modes in urban areas. However, cyclists are vulnerable road users and often suffer severe injuries once crashes occur, which has impeded the growth of bicycle uses. Identification of factors that influence injury severities of crashes involving cyclists can help policy-makers form efficient strategies to mitigate crashes. Moreover, crashes involving cyclists at daytime and nighttime are very likely to present different patterns. Hence, the objective of this study is to explore the underlying factors to injury severity in crashes involving cyclists in the daytime and nighttime separately. Mixed logit model approach is employed due to its advantage of accounting for heterogeneity in observations and four factors are found to have random effects in the mixed logit model for daytime. The differences of crash mechanisms at daytime and nighttime are discussed, and the results of this research would help to develop effective policies that aim to mitigate the injury severities of cyclists while promoting the use of bicycles.

As a cost-effective way to promote healthy eating habits and prevent obesity, nutrition labeling has drawn great public interest around the world. China implemented its first mandatory nutrition labeling regulation under the National Food Safety Standard for Nutrition Labeling of Pre-packaged Foods (GB28050-2011) in 2013. Focusing on the Chinese carbonated soft drinks market and using a mixed logit model based on 132,849 purchase records from over 40,000 households, this study investigates consumers' responses to nutrition labels. Empirical results show that nutrition labeling induces Chinese consumers to select relatively healthier products and could be a prominent policy tool for sugar reduction. [ABSTRACT FROM AUTHOR]

This study investigates factors contributing to the injury severity of truck-involved work zones crashes in South Carolina (SC). The outcome of interest is injury or property damage only crashes, and the explanatory factors examined include the occupant, vehicle, collision, roadway, temporal, and environmental characteristics. Two mixed (random parameter) logit models are developed, one for non-interstates with speed limits less than 60 miles per hour (mph) and one for interstates with speed limits greater than or equal to 60 mph, using South Carolina statewide truck-involved work zone crash data from 2014 to 2020. Results of log-likelihood ratio tests indicate that separate speed models are warranted. The factors that were found to contribute to injury at the 90% confidence level in both models (interstate and non-interstate) are (1) dark lighting conditions, (2) female (at-fault) drivers, and (3) driving too fast for roadway conditions. Significant factors that apply only to non-interstates are SC or US primary roadways, activity area of the work zone, at-fault drivers under 35, sideswipe collision, presence of workers in the work zone, and collision with fixed objects. Significant factors that apply only to interstates are three or more vehicles, rear-end collision, location before the first work zone sign, and weekdays. [ABSTRACT FROM AUTHOR]

Snow removal and deicing using snowplow trucks assist transportation agencies to enhance roadway safety and mobility. However, due to slower travel speeds during these operations, motorists often end up in crashes for poor visibility and disturbance of the snow. Despite the risk associated with snowplows, no previous study was found that exclusively investigate the factors associated with injury severity in snowplow-involved crashes. Therefore, this paper presents an extensive exploratory analysis and fills this knowledge gap by identifying the significant contributing factors affecting the occupant injury severity from the aspects of crashes with snowplow involvement. The study utilized eleven years (2010-2020) of historical snowplow-related crash data from Wyoming. Both the binary logit model and mixed binary logit model were developed to investigate the impacts of the various occupant, vehicle, crash, roadway, and environmental characteristics on the corresponding occupant injury severity. As one of the important findings from this research concludes that other vehicle drivers are more responsible than snowplow drivers contributing to more severe injuries in crashes involving snowplows. Recommendations suggested based on the modeling results are expected to help transportation agencies and policymakers take necessary actions in reducing snowplow-involved crashes by targeting appropriate strategies and proper resource allocation. [ABSTRACT FROM AUTHOR]

This paper firstly analyzes the comparative advantages of carpooling under the mobile Internet and traditional travel modes, including buses, private cars and taxis, as well as the differences between carpooling under the mobile Internet and traditional carpooling, so as to obtain the factors that affect travelers' mode choices. Secondly, the mixed logit model is used to describe the travelers' travel mode choice behavior, which effectively avoids the limitations of the IIA characteristics and preference randomness of the logit model. Finally, we conducted an SP survey on 1077 samples online and offline. After eliminating some invalid samples, 984 valid ones were obtained. Based on these survey data, we analyze the impacts of carpooling under the mobile Internet on the mode shares of traditional travel modes. The results show that for different trip lengths, carpooling under the mobile Internet has different degrees of substitution for buses, taxis and private cars. That is to say, travelers who previously chose buses and other modes will shift to carpooling due to the mobile Internet. In addition, in most cases, the emergence of carpooling under the mobile Internet is helpful to reduce the traffic volume in the urban road network, thus alleviating the urban congestion. However, when the trip length is short and the seat utilization ratio of carpooling under the mobile Internet is low, carpooling under the mobile Internet will increase the traffic volume. [ABSTRACT FROM AUTHOR]

BackgroundIn the treatment of Non-Small Cell Lung Cancer (NSCLC) the combination of Immuno- Oncotherapy (IO) and chemotherapy (CT) has been found to be superior to IO or CT alone for patients’ survival. Patients and clinicians are confronted with a preference sensitive choice between a more aggressive treatment with a greater negative effect on quality of life versus alternatives that are less effective but have fewer side effects.ObjectivesThe aims of this study were to: (a) quantify patients’ preferences for relevant attributes related to Immuno-Oncotherapy treatment alternatives, and (b) evaluate the maximum acceptable risk (MAR)/Minimum acceptable benefit (MAB) that patients would accept for treatment alternatives.MethodsAn online preference survey using discrete-choice experiment (DCE) was completed by NSCLC patients from two hospitals in Italy and Belgium. The survey asked patients’ preferences for five patient- relevant treatment attributes. The DCE was developed using a Bayesian D-efficient design. DCE analyses were performed using mixed logit models. Information regarding patient demographics, health literacy, locus of control, and quality of life was also collected.Results307 patients (158 Italian, 149 Belgian), stage I to IV, completed the survey. Patients preferred treatments with a higher 5-year survival chance as the most important attribute over all the other attributes. Preference heterogeneity for the attribute weights depended on health literacy, patients’ age and locus of control. Patients were willing to accept a substantially increased risks of developing side effects in exchange for the slightest increase (1%) in the chance of surviving at least 5 years from the diagnosis of cancer. Similarly, patients were willing to accept a switch in the mode of administration or complete loss of hair to obtain an increase in survival.ConclusionIn this study, the proportion of respondents who systematically preferred survival over all other treatment attributes was particularly high. Age, objective health literacy and locus of control accounted for heterogeneity in patients’ preferences. Evidence on how NSCLC patients trade between survival and other NSCLC attributes can support regulators and other stakeholders on assessing clinical trial evidence and protocols, based on patients’ conditions and socio-demographic parameters.

The fatal or incapacitating injury caused by overturn crashes involving sport utility vehicles (SUVs) is irreparable. The purpose of this study is to identify potential factors that affect the injury severity of overturn crashes involving SUVs and develop adequate preventive strategies. Given the unobserved heterogeneity existing in the data set, crash data in North Carolina from Highway Safety Information System (HSIS) is analyzed and separated by Latent Class Clustering into six relatively homogeneous groups. To further explore the heterogeneity, random parameter logit models are developed for each cluster, and the impacts of significant factors are estimated with marginal effects. The results reveal the heterogeneity across the clusters and the homogeneity within the same cluster. Variables (including females, people over fifty years old, improper or aggressive behavior, rural areas, high-speed limit, curved roadway, rolling and mountainous terrain, adverse weather, and poor light conditions) are associated with the injury severity of the overturn crashes involving SUVs. The findings of this study can further provide decision makers with insightful countermeasures to improve transportation safety and mitigate the injuries of overturn crashes involving SUVs. [ABSTRACT FROM AUTHOR]