城市居民交通方式选择及其影响因素分析——以南京市为例

随着我国城市化水平的提高,城市交通能源消费占总能源消费的比重逐渐增大,交通方式选择及其影响因素研究引起广泛关注。本研究通过调查南京居民出行交通方式,并通过多项logit模型(multinomial logit model),探究影响居民交通选择的关键因素,为城市交通政策的制定提供科学依据,并根据估算结果分析不同政策下交通方式改变带来的节能减排效应。结果显示:出行特性(如出行距离)、出行者的个人特征(如性别、年龄、职业)与出行者的家庭特征(如是否有私家车,是否有小孩)都对交通方式选择有显著影响。如果通过有效的交通政策引导,使私家车出行转变为轨道交通出行,南京每天大约可减少1573.5吨碳排放。     

微观福利视角下的库区移民搬迁意愿调查

三峡地区社会经济的发展受到资源、环境的限制,又面临再次移民的规划.为有效的缓解由于搬迁中搬迁主体与搬迁规划向左而产生的社会矛盾,优化搬迁政策制度,实现社会的和谐,就应分析库区移民自身的福利状态与搬迁意愿之间的关系.本文在福利理论分析框架下建立理论模型并设计问卷,在多层随机抽样调查的基础上,对理论模型进行验证,运用Logit模型建立三个逐次包含的模型,进行回归分析,试图找到对移民搬迁意愿产生较大影响的福利影响因素,并分析其原因.研究表明,对于库区人口搬迁的自身福利的变化而言,最重要的影响因素为:居住环境、居住方式、教育程度、饮水方式、政策了解程度、环境满意度等;收入、承包地面积、工作等因素也起着一定的影响作用;年龄及基础设施建设中的电话和教育建设对于搬迁意愿的影响则不明显.     

用水协会运行绩效及其影响因素分析——基于江西省3949个用水协会的实证研究

近年来我国用水协会的数量呈爆炸式增长,但学者对其运行绩效及影响因素的研究不够全面和深入。论文使用江西省11个市3 949个用水协会数据,对用水协会的运行绩效及其影响因素进行实证研究。研究表明,是否注册、参与农户数、组建边界、协会主要领导人产生方式、是否有工程产权证、灌溉设施完好率、灌区规模对用水协会运行绩效有显著正影响;而租用和借用办公场所、协会工作人员数、协会起源、协会主要领导人身份则有显著负影响。要使用水协会运行良好,应重视协会的注册工作,完善协会主要领导人产生方式,控制协会工作人员规模,深化小型农田水利工程设施产权制度改革。     

A new baseline model for estimating willingness to pay from discrete choice models

We show a substantive problem exists with the widely-used ratio of coefficients approach to calculating willingness to pay (WTP) from discrete choice models. The correctly calculated standard error for WTP using this approach is shown to be undefined. This occurs because the cost parameter's standard error implies some possibility the true parameter value is arbitrarily close to zero. We propose a simple yet elegant way to overcome this problem by reparameterizing the (negative) cost variable's coefficient using an exponential transformation to enforce the theoretically correct positive coefficient. With it the confidence interval for WTP is now finite and well behaved.     

Investigating the effect of geometric dimensions of median traffic barriers on crashes: Crash analysis of interstate roads in Wyoming using actual crash datasets

IntroductionDespite the numerous safety studies done on traffic barriers’ performance assessment, the effect of variables such as traffic barrier’s height has not been identified considering a comprehensive actual crash data analysis. This study seeks to identify the impact of geometric variables (i.e., height, post-spacing, sideslope ratio, and lateral offset) on median traffic barriers’ performance in crashes on interstate roads.MethodGeometric dimensions of over 110 miles median traffic barriers on interstate Wyoming roads were inventoried in a field survey between 2016 and 2018. Then, the traffic barrier data collected was combined with historical crash records, traffic volume data, road geometric characteristics, and weather condition data to provide a comprehensive dataset for the analysis. Finally, an ordered logit model with random-parameters was developed for the severity of traffic barrier crashes. Based on the results, traffic barrier’s height was found to impact crash severity.ResultsCrashes involving cable barriers with a height between 30″ and 42″ were less severe than other traffic barrier types, while concrete barriers with a height shorter than 32″ were more likely involved with severe injury crashes. As another important finding, the post-spacing of 6.1–6.3 ft. was identified as the least severe range in W-beam barriers.Practical applicationsThe results show that using flare barriers should reduce the number of crashes compared to parallel barriers.     

Examination of factors associated with use rates after transition from a universal to partial motorcycle helmet use law

Objectives: Motorcycle riders account for a disproportionately high number of traffic injuries and fatalities compared to occupants of other vehicle types. Though research has demonstrated the benefits of helmet use in preventing serious and fatal injuries in the event of a crash, helmet use has remained relatively stable in the United States, where the most recent national estimates show a 64% use rate. Use rates have been markedly lower among those states that do not have a universal helmet law for all riders. In 2012, the state of Michigan repealed its longstanding mandatory helmet use law. In order to gain insights as to the effects of this legislative change, a study was conducted to examine short-term changes in helmet use and identify factors associated with use rates.

Methods: A statewide direct observation survey was conducted 1 year after the transition from a universal helmet law to a partial helmet law. A random parameters logistic regression model was estimated to identify motorcyclist, roadway, and environmental characteristics associated with helmet use. This modeling framework accounts for both intravehicle correlation (between riders and passengers on the same motorcycle) as well as unobserved heterogeneity across riders due to important unobserved factors.

Results: Helmet use was shown to vary across demographic segments of the motorcyclist population. Use rates were higher among Caucasian riders, as well as among those age 60 and above. No significant difference was observed between male and female riders. Use was also found to vary geographically, temporally, and with respect to various environmental characteristics. Geographically, helmet use rates tended to be correlated with historical restraint use trends, which may be reflective of riding environment and general differences in the riding population. To this end, rates were also highly variable based upon the type of motorcycle and whether the motorcyclist was wearing high-visibility gear.

Conclusions: The study results demonstrate the short-term reduction in helmet use following transition from a universal to partial motorcycle helmet law. The reduction in use is somewhat less pronounced than has been experienced in other states, which may be reflective of general differences among Michigan motorcyclists because the state has also generally exhibited higher use rates of seat belts and other forms of occupant protection. The study results also highlight potential target areas for subsequent education and public awareness initiatives aimed at increasing helmet use.     

Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model

Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes.     

Investigation of injury severities in single-vehicle crashes in North Carolina using mixed logit models

IntroductionRoadway departure (RwD) crashes, comprising run-off-road (ROR) and cross-median/centerline head-on collisions, are one of the most lethal crash types. According to the FHWA, between 2015 and 2017, an average of 52 percent of motor vehicle traffic fatalities occurred each year due to roadway departure crashes. An avoidance maneuver, inattention or fatigue, or traveling too fast with respect to weather or geometric road conditions are among the most common reasons a driver leaves the travel lane. Roadway and roadside geometric design features such as clear zones play a significant role in whether human error results in a crash. Method: In this paper, we used mixed-logit models to investigate the contributing factors on injury severity of single-vehicle ROR crashes. To that end, we obtained five years' (2010–2014) of crash data related to roadway departures (i.e., overturn and fixed-object crashes) from the Federal Highway Administration's Highway Safety Information System Database. Results: The results indicate that factors such as driver conditions (e.g., age), environmental conditions (e.g., weather conditions), roadway geometric design features (e.g., shoulder width), and vehicle conditions significantly contributed to the severity of ROR crashes. Conclusions: Our results provide valuable information for traffic design and management agencies to improve roadside design policies and implementing appropriately forgiving roadsides for errant vehicles. Practical applications: Our results show that increasing shoulder width and keeping fences at the road can reduce ROR crash severity significantly. Also, increasing road friction by innovative materials and raising awareness campaigns for careful driving at daylight can decrease the ROR crash severity.     

Assessing the relative impacts of the factors affecting MIS adoption process

Micro-irrigation systems (MIS) have been at the forefront of policy-making and social research in exploring determinants that could potentially impact the adoption of MIS technologies in the field to fulfil the basic aim of enhanced agricultural productivity and enriched nutritional quality of the produce with optimal adoption of natural resources. Therefore, this study was undertaken to determine why MIS technologies have not been adopted to the extent anticipated, so that suitable policy schemes, promotional schemes and socio-technical frameworks could be formulated for their enhanced adoption to enhance the socio-economic status of the farming community in the Dahod district of Gujarat State, India. A study of 350 non-MIS (NMIS) and 350 MIS farmers was conducted to identify factors affecting the MIS adoption process. The logit model was fitted using XLSTAT software (XLSTAT 2014.1.04) to the explanatory variables (determinants) of the MIS adoption process. Type III analysis and ANOVA were conducted to test the relative significance of the explanatory variables adopted. It was found that total income had the highest weight (or beta coefficient, i.e. 0.625) followed by total land area (0.546), motor horsepower (0.499), dependency ratio (0.397), and education (0.295) and age of household head (0.207). Furthermore, to assess the efficacy of the logit model, the ROC curve was also developed and the AUC was found to be 0.881, and therefore the model was considered to discriminate well in identifying the factors affecting the MIS adoption process. The study found that higher total income and education level increase the likelihood of MIS adoption and agricultural water management, and therefore special training programmes on installation, as well as repair and maintenance, of MIS systems and agricultural water management can be planned at the institutional/organisation level. The total cultivable area is also one of the important determinants in MIS adoption, and therefore the adoption of MIS schemes should not be restricted to large farmers only, but rather should be extended to both small and marginal farmers.