Investigating and modeling motorcycle crash rates at urban unsignalized intersections in India

OBJECTIVE

The present study focuses on understanding the behavior of motorized 2-wheeler (MTW) riders at urban unsignalized intersections in India. In the Indian context, over 60% of road crash fatalities are attributed to vulnerable road users, with MTWs serving as the predominant contributors, accounting for 44% of total fatalities. Notably, unsignalized intersections have emerged as critical sites for accidents involving vulnerable road users.

METHODS

Postencroachment time is used to assess traffic conflicts of MTW users. Furthermore, the study employs the exceedance property of extreme value theory to calculate crash probabilities. Tobit and grouped random parameters Tobit regression models are developed to model crash probabilities, incorporating variables such as traffic volume, traffic composition, gap acceptance time, intersection characteristics, and intersection conflict area at 4 urban unsignalized intersections in Surat, India.

RESULTS

MTW riders have the lowest gap acceptance time among vehicles in the traffic stream. Cars and other heavy vehicles readily accept gaps when MTWs are in the conflicting stream at unsignalized intersections, which increases traffic conflicts. MTWs have the highest crash rates in the traffic stream. Among the developed models, the grouped random parameters Tobit regression captures the spatial unobserved heterogeneity of the study sites and outperforms the simple Tobit regression model. The results also indicate that MTW riders are exposed to a higher risk of crashes while turning at unsignalized intersections. The presence of a central traffic island has varied implications; it raises crash rates at 3-legged intersections but lowers them at 4-legged intersections for 2-wheelers.

CONCLUSION

The study concludes that MTW crash rates are influenced by traffic and intersectional factors. Increased gap acceptance time correlates with lower crash rates. Countermeasure selections require detailed investigations, because it was observed that the presence of central traffic islands has varied effects on crash rates at 3-legged and 4-legged unsignalized intersections.

Spatiotemporal evolution and influencing factors of China's economic development performance under carbon emission constraints

BACKGROUND

China's high-quality economic development depends on achieving sustainable economic development, reaching peak carbon emissions, achieving carbon neutrality, and intensifying the development of an industrial and energy structure that saves resources and protects the environment. This study used the data envelopment analysis (DEA) model and the Malmquist productivity index to measure the economic development performance of mainland China under carbon emission constraints. Then, it described the spatiotemporal evolution of economic development performance and analyzed its influencing factors using the Tobit model.

RESULTS

The results revealed that there were obvious differences in the trends of the static and dynamic performance of economic development. On the one hand, the static performance of economic development exhibited an upward trend from 2008 to 2020. Its distribution characteristics were dominant in the higher and high-level areas. On the other hand, the dynamic performance had a downward trend from 2008 to 2016 and then an upward trend from 2016 to 2020. In most provinces, the dynamic performance was no longer constrained by technological progress but rather by scale efficiency. It was found that the main factors influencing economic development performance were urbanization level, energy efficiency, vegetation coverage, and foreign investment, while other factors had no significant influence.

CONCLUSIONS

This study suggests that China should improve its economic development performance by increasing the use of clean energy, promoting human-centered urbanization, increasing carbon absorption capacity, and absorbing more foreign capital in the future.

Identifying the evolution of ecological poverty alleviation efficiency and its influencing factors: evidence from counties in Northeast China

Ecological poverty alleviation (EPA) is an effective strategy to address the vicious circle of poverty and environmental destruction in poor areas. However, it remains controversial whether this strategy has really succeeded in this respect. Previous research investigated the impact of a certain factor on EPA, and only few studies integrated them to explore their differential effects, thereby overlooking the complexity of EPA. Therefore, this study quantified the overall efficiency of the EPA strategies of 28 poor counties in three provinces of Northeast China from 2005 to 2018 by using a super-efficiency slacks-based measure model. This model can take into account undesirable outputs; as such, it has significant advantages in measuring the coordination among economic and social development and environmental protection. The Tobit model was used to explore the factors influencing EPA efficiency. The results show that, first, the majority of counties investigated had an EPA efficiency below the overall national average. Second, as for the factors influencing EPA efficiency, it was found that (1) GDP per capita and investment in environmental governance favored EPA efficiency, as they are conducive to stimulating regional consumption dynamics and achieving green economic development; (2) science and technology expenditure and urbanization were not conducive to EPA efficiency; and (3) industrial structure and trade had insignificant effects on EPA efficiency, due to the small scale of industry and the inadequacy of the policy system. This study assessed EPA efficiency from a holistic perspective, and addressed the controversies over EPA's influencing factors, thereby providing an effective method to conduct regional EPA assessment and improve EPA performance in poor regions of China.

Cultivated Land Input Behavior of Different Types of Rural Households and Its Impact on Cultivated Land-Use Efficiency: A Case Study of the Yimeng Mountain Area, China

Analyzing cultivated land input behavior (CLIB) at the scale of rural households links with cultivated land-use efficiency (CLUE), this study examined the Yimeng Mountain area in northern China, supported by field survey data from 737 rural households. This research systematically analyzed the characteristics of CLIB of different types of rural households, measured the CLUE of different types of rural households by using a data envelopment analysis (DEA) model, and explored the influence of CLIB on CLUE based on the Tobit regression model. The results show (1) significant differences in the characteristics of the CLIB of different types of rural households in the Yimeng Mountain area. Among them, the highest land, labor, and capital inputs were I part-time rural households (I PTRH), followed by full-time rural households (FTRH). In contrast, II part-time rural households (II PTRH) and non-agricultural rural households (NARH) had higher levels of non-agricultural employment; however, their input levels gradually declined. (2) The CLUE of the sample rural households was generally low and had considerable potential for improvement. Regarding the types of rural households, as the degree of part-time employment increased, the CLUE showed an inverted U-shaped trend of first increased and then decreased, namely, I PTRH > FTRH > II PTRH > NARH. This finding indicates that appropriate part-time employment could help to promote investment in agricultural production and improve the CLUE. (3) The CLIB of rural households had significant effects on CLUE; the literacy of the agricultural labor force, yield-increasing input per unit area, per capita household income, share of agricultural income, operation scale of cultivated land, effective irrigation rate of cultivated land, and soil and water conservation rate of cultivated land had positive effects on improving CLUE. Even so, there was still significant heterogeneity in the degree of influence of different rural household types. The study concluded with some policy recommendations from the perspective of different rural household types to provide references for optimizing farming inputs and improving CLUE.

What Affects Rural Ecological Environment Governance Efficiency? Evidence from China

With rapid economic development, the protection of the ecological environment has become very important. The modernization of rural ecological governance is the basis and prerequisite for the sustainable economic and social development of vast rural areas of China in the current era. It is urgent to analyze the influencing factors and to improve China’s rural ecological environment governance efficiency for Rural Revitalization in the new era, and to promote the modernization of the national environmental governance system and governance capacity. This paper empirically examines the influencing factors on rural ecological environment governance efficiency in the whole country, and in the eastern, central and western regions separately, at the provincial level, using the Tobit regression model. The results show that, at the national scale, the level of rural economic development, the size of village committees and rural public participation all have positive roles in promoting the efficiency of rural ecological environment governance. Rural population agglomeration, financial support for agriculture. And environmental protection social organizations have negative roles, hindering the efficiency of rural ecological environment governance. From the perspective of the eastern, central, and western regions, the factors affecting the efficiency of rural ecological environment governance are different due to regional differences. According to the results of empirical analysis, it is proposed that the key issue in improving the efficiency of rural ecological environment governance in China is to promote differentiated regional coordinated governance mechanisms.

Industrial three-division network system in China: efficiencies and their impact factors

The industrial production system can be divided into energy consumption (EC), wastewater treatment (WWT), and waste gas treatment (WGT) stages. Based on three stages, this paper presents an empirical investigation on China's industrial efficiencies and the impact factors between 2011 and 2015. Specifically, we apply the network slacks-based measure (SBM) model to evaluate the industrial eco-efficiency, and calculate the division efficiencies via efficiency decomposition approach. Furthermore, the factors affecting the industrial efficiencies are explored through Tobit regression. We find that (1) there is a great potential to improve the eco-efficiency, and for most provinces, the EC efficiencies are highest, followed by the WGT efficiencies, and the WWT efficiencies are the lowest. (2) The efficiencies present obvious area disparities, the eco-efficiency of the eastern area is the highest except for 2012 and 2013, and the eastern area behaves best at the EC stage, while the western area at the WGT stage and the central area fluctuate greatly at the WWT stage. (3) Technological innovation and urbanization level hinder the improvements of eco-efficiency, while economic structure, industrial structure, and economic development level are positive impact factors, especially the industrial structure. Moreover, environmental regulation insignificantly affects the eco-efficiency but exerts a positive effect on the WGT efficiency.

Determination of safe limit for arsenic contaminated irrigation water using solubility free ion activity model (FIAM) and Tobit Regression Model

Irrigation water contaminated with arsenic acts as a potent source of contamination to humans through water-soil-crop-food transfer so quantification of safe limit for irrigation water is also critical. A pot experiment was conducted to determine the safe limit for As contaminated irrigation water with two soil types (alluvial and red) using ten levels of contaminated irrigation water (0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.50, 1.75, 2.0, 2.25 mg L^-1), applied 5 times in rice (Variety: Sushak Samrat),used as a test crop. The results reveal that the different fractions of arsenic in terms of its profusion followed the order F4 > F2 > F5 > F3 > F1 and F4 > F3 > F2 > F5 > F1 across all the doses of As for alluvial soil and red soil respectively. The safe limit of irrigation water in terms of risk assessment expressed as Hazard Quotient (HQ) was at 0.75 mg L^-1 and the solubility FIAM can effectively predict the As content in rice grain in both the soils. The Tobit Regression Model in alluvial soil quantified the safe limit for As in irrigation water from 1.20 to 0.10 mg L^-1 for available soil As 0.25-3.0 mg kg^-1 and in red soil, the range was from 0.10 to 0.40 mg L^-1 for soil As 1.0 to 0.25 mg kg^-1 provided that the As content in rice grain is < 0.4 mg kg^-1. This proved to be an effective protocol for estimation of safe limits after proper validation and calibration.

A new statistical test for latent class in censored data due to detection limit

Biomarkers of interest in urine, serum, or other biological matrices often have an assay limit of detection. When concentration levels of the biomarkers for some subjects fall below the limit, the measures for those subjects are censored. Censored data due to detection limits are very common in public health and medical research. If censored data from a single exposure group follow a normal distribution or follow a normal distribution after some transformations, Tobit regression models can be applied. Given a Tobit regression model and a detection limit, the proportion of censored data can be determined. However, in practice, it is common that the data can exhibit excessive censored observations beyond what would be expected under a Tobit regression model. One common cause is heterogeneity of the study population, that is, there exists a subpopulation who lack such biomarkers and their values are always under the detection limit, and hence are censored. In this article, we develop a new test for testing such latent class under a Tobit regression model by directly comparing the amount of observed censored data with what would be expected under the Tobit regression model. A closed form of the test statistic as well as its asymptotic properties are derived based on estimating equations. Simulation studies are conducted to investigate the performance of the new test and compare the new one with the existing ones including the Wald test, likelihood ratio test, and score test. Two real data examples are also included for illustrative purpose.

A panel analysis of the sustainability of logistics industry in China: based on non-radial slacks-based method

Previous studies have primarily targeted at positive causal linkages between the logistics industry and economic benefits, resulting in biased findings without the consideration of undesirable social and environmental problems. Therefore, this paper aims to develop a holistic approach to the assessment of logistics efficiency, through considering comprehensive inputs and desirable and undesirable outputs. In specific, contextualized in China, this paper comprehensively examined the spatiotemporal variations of China logistics efficiency and further investigated the impact of some exogenous factors. Results indicate that the overall logistics efficiency of China was low, but temporally showed a trend of increase. Spatially, the logistics efficiency followed the pattern of Eastern > Central > Western > Northeastern. Moreover, for the spatial interaction among adjacent provinces, there occurred high-high patterns in the Eastern, and low-low aggregation in the Western and Northeastern regions. However, along with time, the spatial interaction among adjacent provinces was weakening. For exogenous factors, level of economic development, urbanization level, utilization rate of logistics resources, and location advantage had a significant positive impact on SLE, while the effect of labor quality was not significant. Overall, this paper enriches the theoretical understandings of sustainable logistics efficiency evaluation and unbiasedly inform central and local governments with approaches to optimizing logistics efficiency.

Health-related quality of life and its influencing factors for patients with hypertension: evidence from the urban and rural areas of Shaanxi Province, China

Background

Hypertension is an important public health issue in China, but there are few studies on health-related quality of life (HRQoL) for patients with hypertension in China. This study aims to examine the HRQoL as measured by EQ-5D and investigate the factors that influence HRQoL for patients with hypertension in Shaanxi Province, China.

Methods

Data were collected from the Shaanxi’s fifth National Health Service Survey conducted in 2013. EQ-5D was employed to measure the HRQoL for patients with hypertension. The Chinese population-based preference trade-off time (TTO) model was used to convert the EQ-5D values. All descriptive analyses, including demographic characteristics, socio-economic status and clinical characteristics, were stratified by urban and rural residence. Tobit regression model was used to investigate the influencing factors of HRQoL.

Results

A statistically significant difference was observed between the EQ-5D utility scores of urban (0.891) and rural hypertension patients (0.870). The urban hypertension patients showed significantly higher utility scores than the rural patients in three of the five dimensions, namely usual activities, pain / discomfort and anxiety / depression. The influencing factors of HRQoL for hypertension patients in China included age, marital status, education level, employment status, physical activity and medical examination. For patients aged 55 years and above, EQ-5D utility score decreased significantly with increasing age. The EQ-5D score increased with higher education level. Married patients showed a higher EQ-5D score than divorced and widowed patients, and employed patients showed a higher score than unemployed and retired patients. Regular physical activity and medical examination had a positive effect on the HRQoL of hypertension patients.

Conclusions

Our study indicated that urban hypertension patients might have higher HRQoL than rural patients in Shaanxi, China. To enhance HRQoL, it is necessary to strengthen the health education for hypertension patients to improve hypertension prevention and to adopt healthy habits such as regular physical activity. It is also important to strengthen the management and monitoring of hypertension in the elderly, and further implement the free medical examination program for the elderly under the public health programs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-016-1536-x) contains supplementary material, which is available to authorized users.