Modelling Road User Perceptions towards Safety, Comfort, and Chaos at Shared Space: The via Maqueda Case Study, Italy

This study aims to investigate the impacts of perception of infrastructure, sociodemographic characteristics, frequency of road use, and road user perception on safety, comfort, and chaos with respect to shared spaces. The case study area was the Via Maqueda, a shared street in Palermo, Italy. A face-to-face survey was conducted and the answers of 200 of the participants, who use three active travel modes, namely, walking, cycling, and micromobility, were analysed. The results obtained from the ordered logit models suggest that one-unit higher perception of infrastructure will increase safety and comfort perceptions for both walking and cycling. Females feel less safe while walking and less comfortable while cycling at shared spaces compared to males. Increasing the age group by one unit will decrease the safety and comfort perceptions for walking. The participants who use the shared spaces more frequently perceive that they feel more comfortable with cycling. Participants, particularly males, find the shared spaces less chaotic for walking when the perception of infrastructure is higher. Regarding the micromobility use at shared spaces, females feel less comfortable compared to males while using micromobility.

Understanding out-of-pocket spending and financial hardship among patients who succumb to cancer and their caregivers

Background In most countries, including those with national health insurance or comprehensive public insurance, some expenses for cancer treatment are borne by the ill and their families. Objectives This study aims to identify the areas of out-of-pocket (OOP) spending in the last half-year of the lives of cancer patients and examine the extent of that spending; to examine the probability of OOP spending according to patients’ characteristics; and to examine the financial burden on patients’ families. Methods 491 first-degree relatives of cancer patients (average age: 70) who died 3–6 months before the study were interviewed by telephone. They were asked about their OOP payments during the last-half year of the patient's life, the nature of each payment, and whether it had imposed a financial burden on them. A logistic regression and ordered logit models were used to estimate the probability of OOP expenditure and the probability of financial burden, respectively. Results Some 84% of cancer patients and their relatives incurred OOP expenses during the last half-year of the patient’s life. The average levels of expenditure were US$5800on medicines, $8000 on private caregivers, and $2800 on private nurses. The probability of paying OOP for medication was significantly higher among patients who were unable to remain alone at home and those who were less able to make ends meet. The probability of spending OOP on a private caregiver or private nurse was significantly higher among those who were incapacitated, unable to remain alone, had neither medical nor nursing-care insurance, and were older. The probability of a financial burden due to OOP was higher among those unable to remain alone, the incapacitated, and those without insurance, and lower among those with above-average income, those with better education, and patients who died at home. Conclusions The study yields three main insights. First, it is crucial that oncology services provide cancer patients with detailed information about their entitlements and refer them to the National Insurance Institute so that they can exercise those rights. Second, oncologists should relate to the financial burden associated with OOP care at end of life. Finally, it is important to sustain the annual increase in budgeting for technologies and pharmaceuticals in Israel and to allocate a significant proportion of those funds to the addition new cancer treatments to the benefits package; this can alleviate the financial burden on patients who need such treatments and their families.

Logistic and multinomial-logit models: A brief review on their modifications and extensions

The work presents various techniques of the logistic and multinomial-logit modeling with their modifications. These methods are useful for regression modeling with a binary or categorical outcome, structuring in regression and clustering, singular value decomposition and principal component analysis with positive loadings, and numerous other applications. Particularly, these models are employed in the discrete choice modeling and the best-worst scaling known in applied psychology and socio-economics studies.

COVID-19 Lockdown Restrictions and Small Business Survival Strategy: Government Supporting Schemes

From antiquity to the present day, the contribution of small businesses to the economic development of a country is overwhelming. Nowadays, COVID-19 lockdown restrictions have exerted an outrageous impact on small businesses survival. In developing countries where government-supporting capacity is low, the severity is substantial. The present study predicts the impact of COVID-19 lockdown restriction and government supporting schemes on small business survival. To meet this purpose, the study primarily used PLS-SEM and binary logit models. The results confirmed that over 44% of small businesses would fail in the first month of lockdown restriction. Moreover, only 6% have cash reserve to survive twelve months. In this regard, the present study suggested that the government should have to abstain from total lockdown measures, without government-supporting schemes. As such, the study has examined the relative importance of COVID-19 based special loan, suspension of payments, withdrawal of restricted funds, and exemption of tax and penalty payments. Among these supporting schemes, COVID-19 based special loan is the most important government-supporting scheme followed by the suspension of interest and principal payments. However, the exemption of tax payments and withdrawal of restricted funds were not significant.

Pausing the Pandemic: Understanding and Managing Traveler and Community Spread of COVID-19 in Hawaii

In the absence of a vaccine, nonpharmaceutical interventions such as social distancing and travel reductions were the only strategies for slowing the spread of the COVID-19 pandemic. Using survey data from Hawaii ( n = 22,200) collected in March through May of 2020 at the onset of the pandemic, the differences between traveler spreaders who brought the disease into the state and community spreaders were investigated. In addition to describing the demographic attributes and comparing them with attributes of those who were vulnerable to COVID-19, logit models explaining travel behaviors were developed and tested. Traveler spreaders were likely to be male, younger, and returning students. Community spreaders were more likely to be male, essential workers, first responders, and medical personnel at the highest risk of exposure. Using spatial statistics, clusters and hotspot locations of high-risk individuals were mapped. As transportation researchers are in a position to combine their critical analytical capabilities and experience with relevant databases on mobility and the spread of infectious diseases, this analysis could support efforts to respond to and slow the spread of the pandemic.

Can the dual-rating regulation improve the rating quality of Chinese corporate bonds?

We developed a dual-reputational rating shopping model to introduce public and institutional reputations. Investor’s and regulator’s penalty rates are described as public and institutional reputations, respectively. We achieved the available conditions of single-rating and dual-rating regulations to prevent rating inflation in this model. To examine the regulatory effects of different types of regulations on Chinese corporate bond ratings, we utilize panel ordered logit models. Theoretical analysis and empirical tests show that, when the reputation effect is low, the single-rating regulation is better at improving rating quality, and when the reputation effect is high, the dual-rating regulation induces rating agencies to provide more accurate ratings. Compared to the regulatory effects of the single-rating and the multi-rating regulations, the dual-rating regulation most effectively improves the rating quality of corporate bonds and prevents rating inflation.

Disrupting Personal (In)Security? The Role of Ride-Hailing Service Features, Commute Strategies, and Gender in Mexico City

This paper sheds light on the personal security dimension of ride-hailing from a gender perspective. We explore how features of Transportation Network Companies (TNCs) services affect riders perceptions of security when commuting in ride-hailing services, and how general perceptions of fear of crime shape the way people value such features. Moreover, we analyze the strategies women and men are using to enhance their own security in ride-hailing and factors influencing these strategies. We conducted a survey of users of the TNC DiDi in Mexico City. The statistical methods used are structural equation models SEM and ordered logit models OLOGIT. Results show that women are more likely to value the information made available by ride-hailing applications (e.g., knowing your location or knowing driver information) and the presence of a panic button. The value given to information also increases if a person feels insecure in the streets, in a public transit station or in public transit. People who perceive higher insecurity in the streets have increased positive perceptions of the possibility of travelling without transfers. We also find that women are 64.4% less likely to share ride-hailing trips (pooling) and 2.14 times more likely to share details of their trips through their cellphones.