Development of Multivariate Ordered Probit Model to Understand Household Vehicle Ownership Behavior in Xiaoshan District of Hangzhou, China

Ma, Jie; Ye, Xin; Shi, Cheng

doi:10.3390/su10103660

Cited by 15 publications

(14 citation statements)

References 47 publications

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“…A significant ρ indicates interdependence between the error terms. A positive value of ρ is considered “promotive” between the measured pair of equations, while a negative value of ρ is “substitutive” [ 40 ]. The STATA command “mvprobit” was used to estimate the parameters β and ρ .…”

Section: Methodsmentioning

confidence: 99%

Evaluating livestock farmers knowledge, beliefs, and management of arboviral diseases in Kenya: A multivariate fractional probit approach

et al. 2021

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Globally, arthropod-borne virus (arbovirus) infections continue to pose substantial threats to public health and economic development, especially in developing countries. In Kenya, although arboviral diseases (ADs) are largely endemic, little is known about the factors influencing livestock farmers’ knowledge, beliefs, and management (KBM) of the three major ADs: Rift Valley fever (RVF), dengue fever and chikungunya fever. This study evaluates the drivers of livestock farmers’ KBM of ADs from a sample of 629 respondents selected using a three-stage sampling procedure in Kenya’s three hotspot counties of Baringo, Kwale, and Kilifi. A multivariate fractional probit model was used to assess the factors influencing the intensity of KBM. Only a quarter of the farmers had any knowledge of ADs while over four-fifths of them could not manage any of the three diseases. Access to information (experience and awareness), income, education, religion, and distance to a health facility considerably influenced the intensity of farmers’ KBM of ADs in Kenya. Thus, initiatives geared towards improving access to information through massive awareness campaigns are necessary to mitigate behavioral barriers in ADs management among rural communities in Kenya.

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Section: Methodsmentioning

confidence: 99%

Evaluating livestock farmers knowledge, beliefs, and management of arboviral diseases in Kenya: A multivariate fractional probit approach

et al. 2021

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“…In this paper, we use the composite marginal likelihood (CML) estimation method to estimate the multivariate probit model, because the CML method can provide the consistent estimators for both coefficients of explanatory variables and correlations in the error covariance matrix. When the full information maximum likelihood estimation procedure is overly computationally intensive, the composite maximum likelihood method can be an alternative [39,40]. Bhat [41] has demonstrated that the CML method has advantages in computational convenience and stability in spite of some efficiency loss.…”

Section: Modeling Methodologymentioning

confidence: 99%

A Multivariate Modeling Analysis of Commuters’ Non-Work Activity Allocations in Xiaoshan District of Hangzhou, China

Guan

Shi

et al. 2019

Sustainability

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This paper investigates the outdoor non-work activity allocation behaviors of commuters in Xiaoshan District of Hangzhou, China, as well as the underlying relationship among different types of outdoor non-work activities. As per their commute and work schedules, commuters' outdoor non-work activities are classified into six categories and considered as binary dependent variables for modeling analysis, including from home before work, on commute way from home to work, going home during work, going out (not going home) during work, on commute way from work back home, and from home after work. Independent variables include commute attributes, work schedules, sociodemographic attributes, and built-environmental attributes. A multivariate probit model is developed to explore the effects of explanatory variables and capture correlations among unobserved influential factors. The model estimation results show that daily work time, education years, and traffic zone have substantial impacts on commuters' non-work activity allocations. As for the underlying relationship among unobserved factors, a positive correlation is found between the outdoor non-work activities on commute way to and from work, indicating a mutually promotive relationship. All other correlations are negative, indicating other types of non-work activities are mutually substitutive. These findings will help to better understand commuters' behaviors of outdoor activity arrangement subject to the time-space constraint from fixed work schedules, and shed some light on the mechanism of complex work tour formation, so as to guide the development of activity-based travel demand models for commuters.

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“…Based on an ordered probit model, the risk degree model of bridge damage caused by the collision of disabled ships was established and applied to analyze the risk degree of bridge damage [39]. Ma and Jie aimed to understand four types of vehicle ownership within a household, including the automobile, motorcycle, electric bicycle, and human-powered bicycle [40]. The study presented a cross-sectional multivariate ordered probit model with a composite marginal likelihood estimation approach, which accommodated the effects of explanatory variables and captured the dependence among the propensity of households for vehicle ownership.…”

Section: Probit Modelmentioning

confidence: 99%

Risk Evaluation of “Not-In-My-Back-Yard” Conflict Potential in Facilities Group: A Case Study of Chemical Park in Xuwei New District, China

Nie¹,

Zhao²,

Zhang³

et al. 2020

Sustainability

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The social risk of chemical industry park projects attracts much attention, as they are perceived to yield strong environmental risks. This paper systematically evaluates the social risk of Xuwei Chemical Park in China, which was investigated as an example to guide the risk control strategy of conflict in industrial facilities for developing countries. The results show that residents and government departments have a resistance to the risks of the project as a stronger sense of group risk perception (the value is 7 × 10−6) compared with the basic value of 7 × 10−5. By contrast, the low value of group risk perception was evaluated in an enterprise group (7 × 10−4), indicating that the risks of petrochemical projects are often accepted. The expert group’s risk perception regarding petrochemical projects is consistent with the basic value. This is a very interesting finding indicating that the greater the experience, the more the support for petrochemical projects. The knowledge and information from education or experience improve the judgment of the risk of the facility, which increases the individual’s rational assessment comprehension of risk. Moreover, factors that are significantly related to residents’ attitudes are information cognitive factors (trust in information publicity and petrochemical project understanding), and project influencing factors (project planning rationality, quality of life improvement, and economic development satisfaction). Among them, the degree of trust in information disclosure has the highest degree of influence, followed by the level of education, while the satisfaction with economic development has the lowest degree of influence. Therefore, improving the trust of residents in the information disclosure of petrochemical projects should be the core of the government’s risk control policy.

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Development of Multivariate Ordered Probit Model to Understand Household Vehicle Ownership Behavior in Xiaoshan District of Hangzhou, China

Cited by 15 publications

References 47 publications

Evaluating livestock farmers knowledge, beliefs, and management of arboviral diseases in Kenya: A multivariate fractional probit approach

Evaluating livestock farmers knowledge, beliefs, and management of arboviral diseases in Kenya: A multivariate fractional probit approach

A Multivariate Modeling Analysis of Commuters’ Non-Work Activity Allocations in Xiaoshan District of Hangzhou, China

Risk Evaluation of “Not-In-My-Back-Yard” Conflict Potential in Facilities Group: A Case Study of Chemical Park in Xuwei New District, China

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