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Following an earthquake, abnormal travel demand causes traffic congestion and poses significant problems for relief efforts. Research on post-earthquake travel demand is essential for disaster management. An effective disaster management strategy ensures achieving sustainable development goals. This study focused on this critical period and analyzed post-earthquake trip decisions. The city of Elazığ, a region not at risk of tsunami, was used as a case study. A 6.8 magnitude earthquake hit Elazığ in January 2020. After the earthquake, data from 2739 individuals were collected by a household survey conducted face-to-face. The data were segregated into two categories, depending on the earthquake's intensity. The study used a binary logit model to examine the potential factors of trip decisions after an earthquake. The results showed that 75% of participants made at least one trip within 24 h after the earthquake. It was observed that household, building-and disaster-related attributes influence earthquake survivors' trip decisions. The initial location at the time of the earthquake was the most significant factor affecting trip decisions. It was also found that individuals who experienced the earthquake outside their homes in both datasets were more likely to make a trip. Additionally, the dataset with higher earthquake intensity had more significant variables affecting the trip decision. [ABSTRACT FROM AUTHOR]

Parking behavior depends on drivers' choice of parking type and willingness to pay for parking. Generally, the parking type refers to off-street and on-street parking facilities. The main factors affecting the preference for parking types are driver, vehicle, travel, and parking characteristics. Understanding drivers' parking type preference behavior and accurately modeling drivers' tendencies helps develop sustainable parking management policies. This study examines the parking preferences of drivers in Istanbul with binary logit models according to whether they pay for parking. The results of the models show that the number of factors influencing parking type preference is higher for free parking than for paid parking, including driver, vehicle, travel, and parking characteristics. Moreover, some factors in the models affect drivers' parking type preferences differently for paid and free parking. Namely, low-income individuals tend to use on-street parking when parking is free and off-street parking when it is paid. Conversely, individuals who drive small-size vehicles prefer off-street parking for free parking and on-street parking for paid parking. Individuals who prefer off-street parking for free parking expect shorter walking distances to the final destination and parking duration. On the contrary, individuals who choose on-street parking for paid parking anticipate shorter walking distances to the final destination and parking duration. [ABSTRACT FROM AUTHOR]

Forest tickets refer to a type of forest resource usufruct certificate characterized by "cooperative operation, quantification of rights and interests, free circulation, and guaranteed dividends". It is an important means to build a market-oriented mechanism for realizing the value of ecological resources. Incomplete information, based on field survey data from thirteen villages in eight townships (towns) in Sanming City, Fujian Province, China, and a binary logit model were used to explore the moderating effects of factors affecting farmers' willingness to participate in forest ticket trading, the heterogeneity of farmers, and social capital. We found the following: In an environment with incomplete information, farmers' willingness to participate in forest ticket trading is influenced by heterogeneity expectations, social capital, government propaganda, and individual family characteristics. There are certain differences in the influencing factors and degree of farmers' willingness to participate in forest ticket trading among different groups of farmers with different levels of education and part-time employment. Social capital can strengthen the positive impact of income expectations and policy sustainability expectations, and alleviate the negative impact of risk expectations. [ABSTRACT FROM AUTHOR]

After three years of COVID-19 lockdown and restrictions, mobility seems to have returned to normality. However, the pandemic has left changes in the mobility patterns of the Madrid Region produced by new trends emerging from COVID-19. This paper analyzes these changes, focusing on the impacts on public transport use, the effects of telematic activities and the influence of home relocation. The basis of the analysis is a survey conducted from November to December 2022, with more than 15,000 valid responses. The results show that public transport lost 6% of trips. These trips have different transfer rates depending on their geographic location. In the City Center, the majority transferred to active modes. However, the car attracted most of these trips in the Metropolitan Ring. These changes in mobility patterns are partly a consequence of the increase in telematic activities. Teleworking has increased by more than 20% in the Madrid Region and has caused changes in trips per week and trip purpose. In addition, teleworking has caused 18% of home relocations to peripheral zones of the region. This paper investigates through statistical analysis which sociodemographic and spatial factors explain the differences in mobility impacts throughout the zones of the Madrid Region. [ABSTRACT FROM AUTHOR]

In the context of China's forest rights reform, promoting forest land circulation is the key to revitalizing forest land resources and promoting the development of the forestry industry. Based on the theoretical analysis of the effect of farmers' cognition on forest land transfer behavior, data from 790 farmers in typical areas of Chengdu were used for empirical testing with the binary logit model. At the same time, the effects of the cognitive differences of the farmers with different education levels on forest land circulation are discussed. Finally, appropriate instrumental variables were selected to modify the model, and the IV probit model was used to test the endogeneity of the model. The results showed that the (1) farmers' cognition had a significant positive effect on the forest land transfer behavior. Among them, in the order of the degree of impact, were the following: ecological cognition, policy cognition, risk cognition, social regulation, and benefit cognition. (2) Among the groups with different education levels, farmers with lower education levels will consider more aspects than farmers with higher education levels when choosing to transfer forest land. By broadening the research into the cognitive composition of farmers, this study deepens our understanding of the influence of farmers' cognition on forest land transfer behavior. Moreover, it is found that Chinese farmers have strong ecological rationality in addition to economic rationality, and ecological cognition plays a greater role in forest land transfer behavior than benefit cognition, which is of considerable significance for further research on forest land transfer behavior. [ABSTRACT FROM AUTHOR]

With the growing demand for transportation and cargo between cities, the proportion of heavy vehicles in freeway traffic has been increasing in Iran and worldwide during the past decade. The impact of heavy vehicles on crash severity has long been a concern in the crash analysis literature for the prevalence of crashes in freeway traffic. The purpose of this study is to investigate the contribution of heavy vehicles to freeway crashes and uncover other causal factors. Using the comprehensive crash and traffic data from the Qazvin–Tehran freeway in Iran, from 2013 to 2018, 1350 crashes involving heavy vehicles were extracted regarding the weather conditions, weekday, main cause of the crash, driver gender, and culprit side. Considering crash severity calculation, the applied coefficient weights in this study for a person were considered as 3 for an accident resulting in injury and 5 for a fatal crash. A binary logit model was estimated using the data to determine if there was a significant correlation between recognized factors and the likelihood of the crash. The logit modeling results clearly illustrate important relationships between various risk factors and occupant injury, in which heavy vehicles were recognized as one of the most important factors in this study. Other variables associated with crash severity were weather conditions and driver attention. Results indicate that the number of crashes is simultaneously dependent on the total vehicle volume and average speed of heavy vehicles. [ABSTRACT FROM AUTHOR]

Increasing private car ownership and car dependency has led to a low share of walking as an active mode as well as congestion, air pollution, and health problems in developing countries. This paper aims to identify and compare the impacts of a selection of socio-economic, travel-related, and built environment variables on walking likelihood and respondents' sensitivity to the walking distance, both for discretionary and mandatory trips. The analysis drew its origin from 14,463 responses acquired through an extensive travel survey conducted in the city of Qazvin, Iran. The estimated binary logit coefficients show people's heterogeneity in the walking behavior for discretionary and mandatory trips. The results report a higher likelihood of walking on mandatory trips at almost all distances than the discretionary ones. Furthermore, investigating individual heterogeneity in different trip distances reveals that people aged less than 14 are more likely to choose walking on mandatory trips longer than 2400 m. Besides, those aged 25–44 years old or above 65 have less tendency to choose walking on mandatory trips with distances of 2000–2400 m and 800–1200 m, respectively. These findings are almost different on discretionary trips; compared to other age groups, people aged 15–24 years are less likely to choose walking on discretionary trips with a distance of 800–1200 m. Moreover, in trip distances of 1200–1600 m, the elderlies have a greater tendency to choose walking compared to other age groups. Some implications for more sustainable mobility in human-oriented urban environments are also presented and critically discussed. [ABSTRACT FROM AUTHOR]

This study examined the influence of political capital on the migration behavior of peasant households in China's equitable urbanization. While existing research has proven that political capital can increase the wages of migrant workers, leading to a higher possibility of their rural-to-urban migration, the direct impact of political capital on migration behavior has not received sufficient attention. As China is one of the largest emerging economies, the impact of political capital on the economy and political transformation is typical. This paper reports a survey of 1120 farmer households from Xinxiang, a traditional agricultural area in central China. Using a binary logit model to test whether peasant households will migrate and a multinomial logit model to test where they will migrate to, this study examined whether political capital had a significant influence on the migration behavior of peasant households. The results suggest that the peasant households with political capital have a higher possibility of moving to urban areas, even though there is a better habitational option, namely, a new village in the local rural area. This suggests that reducing the difference in the political capital of migrants through policy propaganda and other methods is an efficient and effective way to achieve and improve equitable access to urbanization. [ABSTRACT FROM AUTHOR]

Although the Myanmar Ministry of Agriculture and Irrigation (MOAI) implemented Good Agricultural Practices (GAPs) in rice production, farmers' application of GAPs is decreasing. This study was conducted to examine farmers' perception of GAPs and the determinants of that perception. Data were collected using a structured questionnaire from a random selection of 315 farmers. By applying principal component analysis (PCA) and cluster analysis, the study found that all component technologies of GAPs have relative advantages and visible benefits. However, these component technologies of GAPs in rice production are perceived as relatively difficult to apply by farmers. According to the result of the binary logit model, determinants of farmers' perception were gender, education, farmland size, access to credit, income from crop production, contact with extension agents, receiving agricultural information, and receiving training in GAPs in rice production. Some agricultural policies and extension activities are needed to enhance farmers' perceptions of the compatibility of GAPs in rice production. First, the implementation of GAPs in rice production should focus mainly on low-income farmers who own small amounts of farmland. Second, MOAI should reform the credit plan for farmers who wish to accept GAPs in rice production. Third, extension workers should have regular contact with farmers to enhance farmers' perception of the compatibility of GAPs in rice production. Finally, more agricultural information should be provided, especially for farmers who have larger farms and higher income, concerning the advantages of using GAPs in rice production. [ABSTRACT FROM AUTHOR]

The purchase subsidy policy gives powerful support in battery electric vehicles' (BEVs) market penetration. However, the purchase subsidy is also a huge financial burden for the government, so it can only be considered as a transitional measure and will be canceled gradually. This paper aims to investigate the impact of purchase subsidy phase-out on BEV adoptions and explore alternative incentive policies to continue stimulating BEV adoptions. A stated preference (SP) survey is conducted in Beijing, and a binary logit (BL) model is established to describe how various factors affect BEV adoption preferences. In addition to the factors related to vehicle techniques, the policies of license plate restrictions and driving restrictions are focused due to Beijing's unique external policy environment. The vehicle use subsidy and bus line driving permit are tested as alternative incentive policies against the purchase subsidy decrease. The results show that incentive policies can significantly influence BEV adoption intentions. If the purchase subsidy policy is canceled in Beijing, the BEV choice probability will be reduced from 45.94% to 16.62%. In this case, the vehicle use subsidy needs to be set at the level of 4966 CNY/year (714.3 USD/year) to maintain the original BEV choice probability. [ABSTRACT FROM AUTHOR]

Alleviating traffic congestion and developing sustainable transportation systems in a city can be assisted by promoting environmentally friendly transportation modes such as walking, cycling, and public transport. Strategies for promoting these desirable transportation modes can be identified based on a sound understanding of how commuters choose travel modes. In this study, multi-day commuting travel mode data was used to explore factors that influenced commute mode choice. A multinomial logit model and a binary logit model were proposed to study commuter travel behavior. The results showed the following. (1) Age, gender, and marriage indirectly influence the commute mode choice; (2) The cost of travel mode has little effect on commute mode choice; (3) The probability of commute mode change mainly influences the car mode choice; (4) The number of transfer times and the distance to the nearest public transport stations are main factors that restrict commuters from choosing public transport; (5) The number of bicycles in the family and commute distance are main factors that restrict commuters from choosing cycling for commuting. Based on these findings, several potential measures are demonstrated to policymakers and transportation planners to alleviate traffic congestion and develop sustainable transportation systems. [ABSTRACT FROM AUTHOR]

The rapid development of online car-hailing services (OCSs) has a huge impact on traditional taxi service (TTS) and is triggering a revolution in the taxi industry. Due to the differences in age, monthly income level, etc., travelers' using frequencies of taxi service are different. It is necessary for online car-hailing platforms and traditional taxi companies to know the choice behavior of different types of passengers to enhance competitiveness. Based on the survey data of taxi passengers in Nanjing, China, the passengers are characterized by using frequency per week as infrequent passengers, moderately frequent passengers, and frequent passengers. The group characteristics and the differences among groups are analyzed. Further, three binary logit models are applied to analyze the taxi service choice behavior of different groups. The model results show the significant factors vary among three types of passengers. The result indicates that the impacts of safety level improvement, comfort level improvement and travel cost reduction for OCS on passengers' choice behavior are higher than that of safety level decreasing, comfort level decreasing, and travel cost increasing. Moderately frequent passengers are more sensitive to comfort level than travel cost. The conclusions contribute to both the OCS and TTS business strategies. The results also provide insights into taxi industry management for governments. [ABSTRACT FROM AUTHOR]

The Chinese main air transport network (CMATN) is the framework for air passenger transport in the country. This study uses complex networks and an econometric model to analyze CMATN's evolution and determinants. In terms of overall network structure, the network has always shown small-world properties, with smaller average path lengths (2.06–2.15) and larger clustering coefficients (0.68–0.77), while its cumulative degree distribution follows an exponential function. City passenger volumes conform to the degree power law function, which means that the more destinations a city connects to, the higher its passenger traffic will be. In major hub cities, such as Beijing, Shanghai, and Guangzhou, control power decreases, while Chengdu, Kunming, Chongqing, Xi'an, Urumqi, and other cities play an increasingly important role in CMATN. In terms of main route passenger volumes and formation, increases in GDP and tourism have had a promoting effect, while high-speed rail (HSR) poses a threat to overlapping routes. CMATN is primarily located in the central and eastern regions, focusing on China's economy, tourism, and efficient HSR development. Although the competition from HSR affects the overall network structure of CMATN based on its influence on specific routes, we believe that the impact is limited due to the different transport attributes of the two networks. The research results of this study can become an information source for decision makers and provide a reference for air transport to seek sustainable development. [ABSTRACT FROM AUTHOR]

With the rapid construction of high-speed railways (HSR), the supply structure of the transportation modes in China has changed greatly. In order to seek the sustainable development of HSR and air transport from the perspective of passenger mode choice behavior, this paper applied a binary logit model to explore the mode choice patterns in the Beijing–Shanghai corridor, which has the most successfully operated HSR line in China. By using the data collected in airports and HSR stations in the two cities, passenger flow composition and passenger mode choice behavior was analyzed. It was found that passengers' preference for air transport decreases with the accompanying number of passengers and access time, and increases with income; female passengers and younger passengers have a higher probability of choosing air transport, ceteris paribus; and leisure passengers are more price-sensitive, they tend to travel by air transport when the air transport prices are lower. The study results reveal the travel characteristics of passengers between Beijing–Shanghai and provide information for policy design and infrastructure management. [ABSTRACT FROM AUTHOR]

This study investigates perceived barriers to walking using data collected from 179 randomly-selected adults between the ages of 18 and 92 in Hamilton, Ontario, Canada. A survey (Hamilton Active Living Study) asked questions about socio-demographics, walking, and barriers to walking. A series of binary logit models are estimated for twenty potential barriers to walking. The results demonstrate that different barriers are associated with different sub-groups of the population. Females, senior citizens, and those with a higher body mass index identify the most barriers to walking, while young adults, parents, driver's license owners, and bus pass owners identify the fewest barriers. Understanding who is affected by perceived barriers can help policy makers and health promotion agencies target sub-groups of the population in an effort to increase walking.