Customers' satisfaction towards Addis Ababa City's minibus taxi service

In Addis Ababa, Shared minibus taxis are contributing significantly more than any other form of public transit to meeting the city's transportation needs. But there were limited research done on taxis in general and customer satisfaction with minibus taxis in particular. Therefore, this study aims to assess the satisfaction of minibus taxi customers through a survey questionnaire distributed and collected at taxi stations. Descriptive analysis was used to measure the satisfaction levels/rates of respondents towards each service quality attribute of the minibus taxis. Then, we compared the means value of satisfaction responses followed by factor/principal component analysis. Once the most important satisfaction variables are identified through the factor analysis, an ordered logit model was used to create a relationship between the selected satisfaction variables and the socio-demographic characteristics of taxi riders. The results of the study showed that minibus taxi overload, safety, and security at stations are attributes in which the respondents show greater dissatisfaction. The result of the ordered logit model revealed that the respondents who showed greater dissatisfaction with the taxi drivers and their assistants' behavior are those who had been stolen at least once on a minibus taxi. Also, riders weigh more on the functionality of the service than their comfort and security. Thus, the service providers, Addis Ababa Road Authority, security personnel, and any relevant body should work together on maximizing the customers' satisfaction in minibus taxis.

Investigating changes in travel behavior over time in response to the COVID-19 pandemic

The COVID-19 pandemic has significantly affected travel behavior, including the frequency and mode of travel, with the magnitude and nature of these effects varying over time. This study investigates the nature of these relationships by examining changes in various measures of travel behavior, including weekly driving hours, as well as the frequency of telecommuting, use of ride-sharing services, travel for medical purposes, and use of food delivery services. Self-reported travel data from a representative statewide survey of Michigan residents were used to assess changes in these metrics during the early stages of the pandemic, as well as one year thereafter. Random effects linear regression and ordered logit regression models were estimated and the findings show that various changes in behavior had long-lasting effects, while other behaviors generally reverted back toward pre-pandemic levels. In addition, these changes were found to vary across individuals. For example, significant differences were observed based on socio-demographic characteristics, between urban and rural areas, and amongst individuals with differing views on COVID-19 and related government interventions. In general, the pandemic tended to have less pronounced and sustained effects among younger adults as compared to older age groups. Further, those individuals who were opposed to mandatory COVID-19 vaccines were less likely to change their travel behavior, during both the early and latter stages of the pandemic. Changes were observed consistently across most of the travel metrics of interest. Among these, overall driving hours, travel for medical purposes, and ride-sharing were still lower during the latter stages of the pandemic, while telecommuting and the use of food delivery services reverted nearer to pre-pandemic levels.

COVID-19 and its impact on mental health as a function of gender, age, and income

This paper examines the impact of COVID-19 on the mental health of people from different socioeconomic classes. This has been done by creating an anxiety score, based on responses to a set of questions that were asked as part of a two-round telephonic survey done by Young Lives Data for India. Using this index, anxiety levels have been classified as high, medium, and low. As the dependent variable has an ordered nature, an ordered logit model has been used for regression. According to the results, job loss, death of the family's earning member or mishap in the family, and price increases all contributed to increased anxiety. The analysis indicates that anxiety levels among women were higher than among men because of the increased burden of household chores and childcare responsibilities. Also, anxiety levels were higher among those who perceived themselves as rich or poor as opposed to those who were comfortable in their income group. There was a higher anxiety level among the rich due to income loss and increased household responsibilities. A high percentage of children and elders reported feeling anxious; school closures and a lack of social interaction caused stress. Isolation also plagued the elderly. Furthermore, many students couldn't avail online learning opportunities due to a lack of resources. The government implemented many policies to mitigate these issues, which included those to mitigate the immediate hunger problem.

Desire to work from home: Results of an Irish study

Large levels of working from home (WfH) were induced by social distancing and viral control measures undertaken to mitigate the Covid-19 pandemic. Representing an unpredicted change in the way large amounts of people undertake their day to day work, it is expected that the legacy of this event, in terms of significant alterations to work and commuting patterns will have wide-ranging and long-lasting results. However, how persistent the current trends will be, remains an open question. Therefore, there is a need for a well-represented study of employees' preferences for the post-pandemic future and focus on white-collar workers and their well-established attitudes considering their flexibility in terms of workplace arrangements. This paper presents the results of a survey undertaken in Ireland in the summer of 2021 gauging the desire of office workers to WfH, the format that most appeals to them, the consideration of home relocation based on the ability to WfH, and the factors that may explain such preferences. Results indicate high levels of desire to WfH, either full time or partially, with increased desire to WfH positively correlated to pre-pandemic commute length, and to a perceived increase in work productivity and quality of non-work life as a result of time spent WfH. Additionally, a number of workers state that they may consider home relocation based upon the ability to WfH. These results should be interpreted as the desire to WfH or total addressable market that exists, rather than the likely levels of WfH that will be observed post-Covid.

Working intentions of medical students in response to healthcare workplace violence and descending resources reform in China

BACKGROUND

In order to curb healthcare workplace violence (WPV) and better allocate healthcare resources, China launched the descending resources reform in 2013 and tightened the anti-violence legal environment simultaneously. Medical students are expected to reconsider their working intentions of entering the medical market (inter-market effect) and choosing high- or low-level hospitals (intra-market effect) in response to the evolving WPV. The goal of this study was to explore the link between the perceived WPV incidence and medical students' willingness to practice medicine in the context of China's descending resources reform.

METHOD

Medical students were selected with cluster sampling from 8 medical colleges in Zhejiang Province, China, and 1497 valid questionnaires were collected by using a five-point unbalanced scale, to perform cross-sectional empirical research using the ordered logit model (OLM).

RESULTS

The perceived WPV incidence negatively correlate with the willingness of medical students to practice medicine but positively correlate with their willingness to practice in low-level hospitals, indicating the existence of inter- and intra-market effects. The anti-violence legal environment has no direct link with working intention but contributes to the perceived decline in the incidence of violence. Descending resources reform has simultaneous opposite effects on medical students, with the coexistence of prudent motives driven by reform costs and optimistic expectations of sharing external benefits.

CONCLUSIONS

Safety needs and risk aversion motive play an important role in medical students' career choice when facing severe WPV. Tightening of the anti-violence legal environment and the descending resources reform could drive medical students to low-level hospitals.

How has the COVID-19 pandemic affected the use of ride-sourcing services? An empirical evidence-based investigation for the Greater Toronto Area

The ongoing COVID-19 pandemic has fundamentally changed the nature of day-to-day life in cities worldwide. In the transportation sector, COVID-19 appears to have impacted modal preferences. In particular, people seem to be less willing to use modes where they may encounter strangers (such as public transit) and modes that involve coming into contact with shared surfaces (such as ride-sourcing). Given the transformative impact that ride-sourcing services had on urban mobility before the pandemic, it is crucial to understand the effects of COVID-19 on the use of ride-sourcing moving forward. Using data from a web-based survey, this study combines descriptive analysis with the application of a two-stage ordered logit model framework to investigate the impacts of COVID-19 on the utilization of ride-sourcing services in the Greater Toronto Area, including how often ride-sourcing is used and the earliest stage of the pandemic that a person would consider using ride-sourcing. Generally speaking, the use of ride-sourcing has decreased since the start of the pandemic, however, there are also people who are using ride-sourcing more often than they did before the pandemic. The results indicate that the perception of risk, the tendency to take precautions when leaving home, and socio-economic factors influence the earliest stage of the pandemic where a person would consider using ride-sourcing. Overall, it appears that ride-sourcing usage will gradually increase as restrictions are lifted; however, it is unlikely to return to pre-pandemic levels until COVID-19 is no longer considered a public health threat.

Corporate ownership concentration drivers in a context dominated by private SME's

This paper aims to ascertain how company-specific factors influence the corporate ownership concentration of Portuguese firms. The paper employs several different regression techniques: Generalized Linear Model, Ordered Logit, 2 Stage Least Squares, Ordinary Least Squares, Truncated and Constrained regression. Additionally, to test the model's prediction power, it conducts an in and out-of-sample analysis and used joint-rolling window regressions and dependent variables intervals partition to test the robustness of the model under different sample restrictions. Firm size, profitability, the number of subsidiaries, and bank concentration are positive determinants of ownership concentration, while an opposite influence is found concerning auditor qualification and the board of directors' size. Significant implications are provided for the policymaking in countries where capital markets are underdeveloped, and concentrated ownership is common to help the regulator determining the power of controlling shareholders. This study enriches the literature on the determinants of corporate ownership, being the first study to approach non-public companies. It adds novelty by incorporating new company factors which are scarce in ownership studies.

How does air quality affect residents' life satisfaction? Evidence based on multiperiod follow-up survey data of 122 cities in China

Since entering the new era, China's socialist contradiction has been transformed into the contradiction between the people's growing need for a better life and the unbalanced and inadequate development. How to improve the quality of people's life through the improvement of air quality has become an important content restricting social development and a key problem to be solved. Based on the life satisfaction (LS) method, this study takes air quality into the individual utility function, and through matching China Health and Retirement Longitudinal Study (CHARLS), two phases of microindividual tracking data with 122 urban environmental quality data innovatively investigate the impact of air quality on residents' LS and its income substitution effect. The results show that air quality significantly reduces residents' LS, among which, different air pollutants and comprehensive air quality AQI have significant negative effects. And PM10 has the highest marginal effect on different LS evaluation, SO2 has the smallest marginal effect, and AQI marginal effect is close to PM10. In terms of group heterogeneity, NO2 and SO2 have group influence differences in age group, regional economic group, gender group, and family per capita income group. But PM10 and AQI do not show group influence heterogeneity, and air quality has significant negative effect on LS of different groups. In addition, the interaction between air quality and income level shows that air quality strengthens the difference of residents' LS caused by income level difference. According to the equilibrium condition of residents' individual utility function, the improvement of air quality by 1% is equivalent to the improvement of residents' LS by 23.4402% of income. Firstly, air quality has an important impact on residents' LS, and different air pollutants have different effects. Secondly, the impact of air quality on LS of different groups is heterogeneous and mainly diversified in age group, regional economic group, gender group, and family per capital income group. Finally, there is substitution effect between air quality and regional GDP growth and household income, which affects residents' LS. Thirdly, the conclusion shows that the improvement of air quality is difficult to be replaced by other ways. Good air quality can not only directly improve residents' LS, but also has economic effect.

Socio-economic predictors of public understanding of the COVID-19 pandemic

The COVID-19 (Coronavirus 2019) pandemic has proven to be the biggest global shock since World War II. That war resulted in 5.5 million deaths. The number of COVID-19-infected persons exceeded 13 million in the first 6 months of the pandemic and many more asymptomatic cases are undocumented. The global economy has been affected severely. The tension, the fear, the drastic measures to try to control the spread of the disease disrupted everyone's life from child to senior. The condition is worse in the global south, such as in Bangladesh, where the average population density is 7.5 times higher than that of China, where COVID-19 began and spread uncontrollably at the end of 2019. Lockdowns and social distancing were tried to stop the transmission of the disease but were often not observed faithfully or were less effective than thought to be. People need to trade and interact to earn money to survive but these activities could endanger others' lives if they do not maintain safety measures. Individual awareness is not only curtailing the spread of COVID-19 but also saves others' lives. This cross-sectional study used Ordinal and Binary logit models to predict the level of awareness through potential regressors of the citizen toward COVID-19 in Bangladesh. Findings of the study are that the level of awareness is dependent on the level of trauma; also, that household income is a statistically-significant predictor of awareness. Behavioral activities such as use of masks, outdoor activities, and stockpiling tendencies are found to be statistically significant predictors of awareness as well.

Resident risk attitude analysis in the decision-making management of waste incineration construction

Environmental pollutants generated by waste incineration plants, such as heavy metals and dioxin, make surrounding residents very sensitive to the construction of such facilities. This sensitivity and anxiety of residents may induce group events, which further leads to the emergence of social risks. Based on risk perception theory, a total of 320 questionnaires was designed and handed out to residents neighboring to Jiangqiao Waste Incineration Plant in Shanghai, China to detect the factors affecting risk attitude toward such plants. Using ordered logit model, it is found that there are four decisive factors including impact on health, information cognitive, objective characteristics, and the attitude of the neighbors. These factors have different influence on resident risk attitudes, in which the attitude of the neighbors is of most significance, followed by the economic-geography characteristics of residents, the information cognitive has minimal impact.

Methods to rank traffic rule violations resulting in crashes for allocation of funds

Education, enforcement and engineering countermeasures are implemented to make road users comply with the traffic rules. Not all the traffic rule violations can be addressed nor countermeasures be implemented at all unsafe locations, at once, due to limited funds. Therefore, this study aims at ranking the traffic rule violations resulting in crashes based on individual ranks, such as 1) frequency (expressed as a function of the number of drivers violating a traffic rule and involved in crashes), 2) crash severity, 3) total crash cost, and, 4) cost severity index, to assist transportation system managers in prioritizing the allocation of funds and improving safety on roads. Crash data gathered for the state of North Carolina was processed and used in this study. Variations in the ranks of traffic rule violations were observed when individual ranking methods are used. As an example, exceeding authorized speed limit and driving under the influence of alcohol are ranked 1st and 2nd based on crash severity while failure to reduce speed and failure to yield the right-of-way are ranked 1st and 2nd based on frequency. To minimize the variations and capture the merits of individual ranking methods, four different composite ranks were computed by combining selected individual ranks. The computed averages and standard deviations of absolute rank differences between composite ranks is lower than those obtained from individual ranks. The weights to combine the selected individual ranks have a marginal effect on the computed averages and standard deviations of absolute rank differences. Combining frequency and crash severity or cost severity index, using equal weights, is recommended for prioritization and allocation of funds.

Associations of distraction involvement and age with driver injury severities

INTRODUCTION

This paper investigates the associations between the severity of injuries sustained by a driver who is involved in a two-vehicle crash, the existence and type of driver distraction as well as driver's age. Few studies investigated distraction as it relates to injury severity. Moreover, these studies did not consider driver age which is a significant factor related to driving behavior and the ability to respond in a crash situation.

METHODS

An ordered logit model was built to predict injury severity sustained by drivers using data from the U.S. National Automotive Sampling System's General Estimates System (2003 to 2008). Various factors (e.g., weather, gender, and speeding) were statistically controlled for, but the main focus was on the interaction of driver age and distraction type.

RESULTS

The trends observed for young and mid-age drivers were similar. For these age groups, dialing or texting on the cell phone, passengers, and in-vehicle sources resulted in an increase in a likelihood of more severe injuries. Talking on the cell phone had a similar effect for younger drivers but was not significant for mid-age drivers. Inattention and distractions outside the vehicle decreased the odds of severe injuries. For older drivers, the highest odds of severe injuries were observed with dialing or texting on a cell phone, followed by in-vehicle sources and talking on the cell phone. All these sources were associated with an increased likelihood of injury severity. Similar to young and mid-age drivers, distractions outside the vehicle decreased the odds of severe injuries. Other distraction types did not have a significant effect for the older age group.

CONCLUSIONS

The results support previous literature and extend our understanding of crash injury severity.

PRACTICAL APPLICATIONS

The findings have implications for policy making and the design of distraction mitigation systems.

Partial proportional odds model-an alternate choice for analyzing pedestrian crash injury severities

The conventional methods for crash injury severity analyses include either treating the severity data as ordered (e.g. ordered logit/probit models) or non-ordered (e.g. multinomial models). The ordered models require the data to meet proportional odds assumption, according to which the predictors can only have the same effect on different levels of the dependent variable, which is often not the case with crash injury severities. On the other hand, non-ordered analyses completely ignore the inherent hierarchical nature of crash injury severities. Therefore, treating the crash severity data as either ordered or non-ordered results in violating some of the key principles. To address these concerns, this paper explores the application of a partial proportional odds (PPO) model to bridge the gap between ordered and non-ordered severity modeling frameworks. The PPO model allows the covariates that meet the proportional odds assumption to affect different crash severity levels with the same magnitude; whereas the covariates that do not meet the proportional odds assumption can have different effects on different severity levels. This study is based on a five-year (2008-2012) national pedestrian safety dataset for Switzerland. A comparison between the application of PPO models, ordered logit models, and multinomial logit models for pedestrian injury severity evaluation is also included here. The study shows that PPO models outperform the other models considered based on different evaluation criteria. Hence, it is a viable method for analyzing pedestrian crash injury severities.

Analysis of injury severity of drivers involved in single- and two-vehicle crashes on highways in Ontario

This study analyzes driver's injury severity in single- and two-vehicle crashes and compares the effects of explanatory variables among various types of crashes. The study identified factors affecting injury severity and their effects on severity levels using 5-year crash records for provincial highways in Ontario, Canada. Considering heteroscedasticity in the effects of explanatory variables on injury severity, the heteroscedastic ordered logit (HOL) models were developed for single- and two-vehicle crashes separately. The results of the models show that there exists heteroscedasticity for young drivers (≤30), safety equipment and ejection in the single-vehicle crash model, and female drivers, safety equipment and head-on collision in the two-vehicle crash models. The results also show that young car drivers have opposite effects between single-car and car-car crashes, and sideswipe crashes have opposite effects between car-car and truck-truck crashes. The study demonstrates that separate HOL models for single-vehicle and different types of two-vehicle crashes can identify differential effects of factors on driver's injury severity.