In this paper, we explore the properties of a positive-part Stein-like estimator which is a stochastically weighted convex combination of a fully correlated parameter model estimator and uncorrelated parameter model e...In this paper, we explore the properties of a positive-part Stein-like estimator which is a stochastically weighted convex combination of a fully correlated parameter model estimator and uncorrelated parameter model estimator in the Random Parameters Logit (RPL) model. The results of our Monte Carlo experiments show that the positive-part Stein-like estimator provides smaller MSE than the pretest estimator in the fully correlated RPL model. Both of them outperform the fully correlated RPL model estimator and provide more accurate information on the share of population putting a positive or negative value on the alternative attributes than the fully correlated RPL model estimates. The Monte Carlo mean estimates of direct elasticity with pretest and positive-part Stein-like estimators are closer to the true value and have smaller standard errors than those with fully correlated RPL model estimator.展开更多
The consequences of flight delay can significantly impact airports’ on‐time performance and airline operations, which have a strong positive correlation with passenger satisfaction. Thus, an accurate investigation o...The consequences of flight delay can significantly impact airports’ on‐time performance and airline operations, which have a strong positive correlation with passenger satisfaction. Thus, an accurate investigation of the variables that cause delays is of main importance in decision-making processes. Although statistical models have been traditionally used in flight delay analysis, the presence of unobserved heterogeneity in flight data has been less discussed. This study carried out an empirical analysis to investigate the potential unobserved heterogeneity and the impact of significant variables on flight delay using two modeling approaches. First, preliminary insight into potential significant variables was obtained through a random parameter logit model (also known as the mixed logit model). Then, a Support Vector Machines (SVM) model trained by the Artificial Bee Colony (ABC) algorithm, was employed to explore the non-linear relationship between flight delay outcomes and causal factors. The data-driven analysis was conducted using three-month flight arrival data from Miami International Airport (MIA). A variable impact analysis was also conducted considering the black-box characteristic of the SVM and compared to the effects of variables indented through the random parameter logit modeling framework. While a large unobserved heterogeneity was observed, the impacts of various explanatory variables were examined in terms of flight departure performance, geographical specification of the origin airport, day of month and day of week of the flight, cause of delay, and gate information. The comprehensive assessment of the contributing factors proposed in this study provides invaluable insights into flight delay modeling and analysis.展开更多
Despite the number of studies focusing on the financial analysis of production activities, conducting on technical solutions, and improving water quality, no study has been conducted on the application of economic ins...Despite the number of studies focusing on the financial analysis of production activities, conducting on technical solutions, and improving water quality, no study has been conducted on the application of economic instruments that apply to water quality management in craft villages, and several studies of WTP also. This study aimed to estimate the households’ willingness-to-pay for wastewater treatment in selected traditional agro-food processing villages in Nhue-Day River Basin, Vietnam. A pilot Choice Experiment (CE) technique in Choice Modelling (CM) approach was applied for this study with 267 selected agro-food processing households by using the conditional logit (CL) and random parameter logit (RPL) models. The results showed that total annual environmental fee for wastewater treatment from agro-food processing households is estimated as 1089 million VND (equal to US$47,868 per year) for the total of 902 agro-food processing households in three research sites in Nhue-Day River Basin. This estimated budget for wastewater treatment accounted for 55.85% of total annual operation and maintenance costs only. In addition, the technology is improved to enable 90% of treated wastewater. Overall, the results of this study suggest the new wastewater treatment plant construction and improved wastewater collection system by increasing the investment in order to improve the water quality in Nhue-Day River Basin that brings about the reducing environmental degradation, biodiversity loss and human health risks.展开更多
Improper lane-changing behaviours may result in breakdown of traffic flow and the occurrence of various types of collisions.This study investigates lane-changing behaviours of multiple vehicles and the stimulative eff...Improper lane-changing behaviours may result in breakdown of traffic flow and the occurrence of various types of collisions.This study investigates lane-changing behaviours of multiple vehicles and the stimulative effect on following drivers in a consecutive lanechanging scenario.The microscopic trajectory data from the HighD dataset are used for driving behaviour analysis.Two discretionary lane-changing vehicle groups constitute a consecutive lane-changing scenario,and not only distance-and speed-related factors but also driving behaviours are taken into account to examine the impacts on the utility of following lane-changing vehicles.A random parameters logit model is developed to capture the driver’s psychological heterogeneity in the consecutive lane-changing situation.Furthermore,a lane-changing utility prediction model is established based on three supervised learning algorithms to detect the improper lane-changing decision.Results indicate that 1)the consecutive lane-changing behaviours have a significant negative effect on the following lane-changing vehicles after lane change;2)the stimulative effect exists in a consecutive lane-change situation and its influence is heterogeneous due to different psychological activities of drivers;and 3)the utility prediction model can be used to detect an improper lane-changing decision.展开更多
文摘In this paper, we explore the properties of a positive-part Stein-like estimator which is a stochastically weighted convex combination of a fully correlated parameter model estimator and uncorrelated parameter model estimator in the Random Parameters Logit (RPL) model. The results of our Monte Carlo experiments show that the positive-part Stein-like estimator provides smaller MSE than the pretest estimator in the fully correlated RPL model. Both of them outperform the fully correlated RPL model estimator and provide more accurate information on the share of population putting a positive or negative value on the alternative attributes than the fully correlated RPL model estimates. The Monte Carlo mean estimates of direct elasticity with pretest and positive-part Stein-like estimators are closer to the true value and have smaller standard errors than those with fully correlated RPL model estimator.
文摘The consequences of flight delay can significantly impact airports’ on‐time performance and airline operations, which have a strong positive correlation with passenger satisfaction. Thus, an accurate investigation of the variables that cause delays is of main importance in decision-making processes. Although statistical models have been traditionally used in flight delay analysis, the presence of unobserved heterogeneity in flight data has been less discussed. This study carried out an empirical analysis to investigate the potential unobserved heterogeneity and the impact of significant variables on flight delay using two modeling approaches. First, preliminary insight into potential significant variables was obtained through a random parameter logit model (also known as the mixed logit model). Then, a Support Vector Machines (SVM) model trained by the Artificial Bee Colony (ABC) algorithm, was employed to explore the non-linear relationship between flight delay outcomes and causal factors. The data-driven analysis was conducted using three-month flight arrival data from Miami International Airport (MIA). A variable impact analysis was also conducted considering the black-box characteristic of the SVM and compared to the effects of variables indented through the random parameter logit modeling framework. While a large unobserved heterogeneity was observed, the impacts of various explanatory variables were examined in terms of flight departure performance, geographical specification of the origin airport, day of month and day of week of the flight, cause of delay, and gate information. The comprehensive assessment of the contributing factors proposed in this study provides invaluable insights into flight delay modeling and analysis.
基金Southeast Asia Regional Center for Graduate Study and Research Agriculture(SEARCA)provide me the financial support to conduct this research.
文摘Despite the number of studies focusing on the financial analysis of production activities, conducting on technical solutions, and improving water quality, no study has been conducted on the application of economic instruments that apply to water quality management in craft villages, and several studies of WTP also. This study aimed to estimate the households’ willingness-to-pay for wastewater treatment in selected traditional agro-food processing villages in Nhue-Day River Basin, Vietnam. A pilot Choice Experiment (CE) technique in Choice Modelling (CM) approach was applied for this study with 267 selected agro-food processing households by using the conditional logit (CL) and random parameter logit (RPL) models. The results showed that total annual environmental fee for wastewater treatment from agro-food processing households is estimated as 1089 million VND (equal to US$47,868 per year) for the total of 902 agro-food processing households in three research sites in Nhue-Day River Basin. This estimated budget for wastewater treatment accounted for 55.85% of total annual operation and maintenance costs only. In addition, the technology is improved to enable 90% of treated wastewater. Overall, the results of this study suggest the new wastewater treatment plant construction and improved wastewater collection system by increasing the investment in order to improve the water quality in Nhue-Day River Basin that brings about the reducing environmental degradation, biodiversity loss and human health risks.
基金sponsored by the National Natural Science Foundation of China (Grant No.71901223)the Natural Science Foundation of Hunan Province (Grant No.2021JJ40746)the Postgraduate Research and Innovation Project of Central South University (Grant No.1053320216523).
文摘Improper lane-changing behaviours may result in breakdown of traffic flow and the occurrence of various types of collisions.This study investigates lane-changing behaviours of multiple vehicles and the stimulative effect on following drivers in a consecutive lanechanging scenario.The microscopic trajectory data from the HighD dataset are used for driving behaviour analysis.Two discretionary lane-changing vehicle groups constitute a consecutive lane-changing scenario,and not only distance-and speed-related factors but also driving behaviours are taken into account to examine the impacts on the utility of following lane-changing vehicles.A random parameters logit model is developed to capture the driver’s psychological heterogeneity in the consecutive lane-changing situation.Furthermore,a lane-changing utility prediction model is established based on three supervised learning algorithms to detect the improper lane-changing decision.Results indicate that 1)the consecutive lane-changing behaviours have a significant negative effect on the following lane-changing vehicles after lane change;2)the stimulative effect exists in a consecutive lane-change situation and its influence is heterogeneous due to different psychological activities of drivers;and 3)the utility prediction model can be used to detect an improper lane-changing decision.
