Optimizing the Cleaning and Disinfection Scheme for Dockless Shared Bikes

Shared bikes can help cities achieve carbon neutrality goals. Cleaning and disinfection are vital procedures of the maintenance of shared bikes, especially during the COVID-19 pandemic because shared bikes could be a transmission intermediary of viruses. This study proposes an optimization model of the cleaning and disinfection scheme of the dockless shared bikes. The disinfection is assumed to be performed at night, when the usage is lowest. By regarding the disinfection staff as traveling salesmen, the model is formulated as an extension of the Multidepot Multiple Traveling Salesman Problem (MDMTSP). The objective function is to minimize the total cost;which consists of the cost associated with the working time and per-capita cost of the disinfection staff. A heuristic algorithm combining k -means clustering and genetic algorithm (K-GA) is adopted to find the lower bound solution. Then, the K-GA-adjustment algorithm has been adopted to find the solutions that satisfy the constraints. To reduce the computing time needed, an approximate function for the lower bound of the optimal number of disinfection staff is obtained by constructing a Continuous Approximation (CA) model. A case study based on real location data of shared bikes in Chengdu, China, is performed to show how the maintenance department could adopt the optimization framework to design an efficient scheme to clean and disinfect the shared bikes. [ABSTRACT FROM AUTHOR] Copyright of Journal of Advanced Transportation is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

COVID-19 moderates the association between to-metro and by-metro accessibility and house prices

Previous studies extensively examined the role of accessibility to metro in shaping house prices but largely overlooked the contribution of accessibility by metro. In addition, limited studies examined the moderating effect of COVID-19 on the price effects of to-metro and by-metro accessibility. Based on multilevel hedonic price and quantile regression models, this study scrutinizes the association between to-metro accessibility, by-metro accessibility, and house prices in Chengdu, China, and examines the moderating role of COVID-19 in this association. We show that by-metro accessibility significantly influences house prices. COVID-19 significantly influences the value of to-metro accessibility but marginally affects that of by-metro accessibility. The value of to-metro accessibility is disproportionately affected by the pandemic. Specifically, small or low-priced houses are less affected than big or high-priced houses. In other words, the flattening of the to-metro price gradient is more discernible for big or high-priced houses. The changing preference of residents has also been verified by the decreases in house transaction volume in metro-adjacent areas.

Exploring the Spatially Heterogeneous Effects of the Built Environment on Bike-Sharing Usage during the COVID-19 Pandemic

Bike-sharing holds promise for available and healthy mobility services during COVID-19 where bike sharing users can make trips with lower health concerns due to social distancing compared to the restricted transportation modes such as public transit and ridesharing services. Leveraging the trip data of the Divvy bike-sharing system in Chicago, this study exploresspatially heterogeneous effects of built environment on bike-sharing usage under the pandemic. Results show that the average weekly ridership declined by 52.04%. To account for the spatially heterogeneous relationship between the built environment and the ridership, the geographically weighted regression (GWR) model and the semiparametric GWR (S-GWR) model are constructed. We find that the S-GWR model outperforms the GWR and the multiple linear regression models. The results of the S-GWR model indicate that education employment density, distance to subway, COVID-19 cases, and ridership before COVID-19 are global variables. The effects between ridership and the built environment factros (i.e., household density, office employment density, and the ridership) vary across space. The results of this study could provide a useful reference to transportation planners and bike-sharing operators to determine the high bike-sharing demand area under the pandemic,thus adjusting station locations, capacity, and rebalancing schemes accordingly.

Impact of COVID-19 on Mental Health of Chinese Residents in Its Initial Stage.

This study aims to investigate the effect of coronavirus disease 2019 (COVID-19) on the Chinese public's mental health during its early stage. We collected the data through an online questionnaire survey. Specifically, we adopted the impact of event scale-revised (IES-R) and state-trait anxiety inventory (STAI) to assess symptomatic responses to exposure to traumatic life events and public anxiety, respectively, in the COVID-19 pandemic outbreak. Then, we evaluated the differences in the scores among various socio-demographic groups using Kruskal-Wakkis H tests and t-tests and analyzed the IES-R, state anxiety (SA) score, and trait anxiety (TA) score using the Pearson correlation analysis. Finally, we conducted a path analysis to determine the mediating role of post-traumatic stress disorder symptoms (measured by the IES-R) in the relationship between TA and SA. The results show that the average of the SA and TA scores were 48.0 ± 10.4 and 38.0 ± 8.2, respectively; the respondents who suffered from mild, moderate, and severe psychological impacts because of the health crisis accounted for 21.9, 5.2, and 13.1%, respectively; farmers have the highest IES-R score than others; people with the highest income have the lowest SA level; a significant positive correlation existed between the IES-R and STAI scores; and TA produces both direct and indirect (through the IES-R) effects on SA. Overall, the general Chinese public exhibited much higher anxiety levels than normal in the early days of the pandemic outbreak. Accordingly, we strongly recommend psychological counseling and intervention support to mitigate the adverse psychological impacts of such an event.

Video conferencing software selection based on hybrid MCDM and cumulative prospect theory under a major epidemic

The video conferencing software is regarded as a significant tool for social distancing and getting incorporations up and going. Due to the indeterminacy of epidemic evolution and the multiple criteria, this paper proposes a video conferencing software selection method based on hybrid multi-criteria decision making (HMCDM) under risk and cumulative prospect theory (CPT), in which the criteria values are expressed in various mathematical forms (e.g., real numbers, interval numbers, and linguistic terms) and can be changed with natural states of the epidemic. Initially, the detailed description of video conferencing software selection problem under an epidemic are given. Subsequently, a whole procedure for video conferencing software selection is conducted, the approaches for processing and normalizing the multi-format evaluation values are presented. Furthermore, the expectations provided by DMs under different natural states of the epidemic are considered as the corresponding reference points (RP). Based on this, the matrix of gains and losses is constructed. Then, the prospect values of all criteria and the perceived probabilities of natural states are calculated according to the value function and the weighting function in CPT respectively. Finally, the proposed method is illustrated by an empirical case study, and the comparison analysis and the sensitivity analysis for the loss aversion parameter are conducted to prove the effectiveness and robustness. The results show that considering the psychological characteristics of DMs in selection decision is beneficial to avoid the unacceptable and potential loss risks. This study could provide a useful guideline for managers who intend to select appropriate video conferencing software. [ABSTRACT FROM AUTHOR] Copyright of Journal of Intelligent & Fuzzy Systems is the property of IOS Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)