Pub Date : 2024-11-02DOI: 10.1016/j.cstp.2024.101314
In 2022 the COVID-19 pandemic coincided with a surge in global fuel prices, particularly affecting Italy. This study explores the impact of rising fuel costs on public transportation usage and its influence on the spread of airborne viruses. As fuel prices increased, private vehicle users were incentivized to shift to public transportation, raising concerns about a potential rise in COVID-19 cases. Using a hybrid model with F-GLS estimators, we find that higher fuel prices are correlated with increased COVID-19 cases, though this effect diminishes with greater public transportation availability. We estimate that when public transportation capacity falls below 6,500 seats per capita per kilometre, case numbers rise. Thus, robust public transportation systems may help limit the spread of airborne viruses, while inadequate systems could exacerbate transmission.
{"title":"Fuelling the pandemic: The impact of fuel prices on COVID-19","authors":"","doi":"10.1016/j.cstp.2024.101314","DOIUrl":"10.1016/j.cstp.2024.101314","url":null,"abstract":"<div><div>In 2022 the COVID-19 pandemic coincided with a surge in global fuel prices, particularly affecting Italy. This study explores the impact of rising fuel costs on public transportation usage and its influence on the spread of airborne viruses. As fuel prices increased, private vehicle users were incentivized to shift to public transportation, raising concerns about a potential rise in COVID-19 cases. Using a hybrid model with F-GLS estimators, we find that higher fuel prices are correlated with increased COVID-19 cases, though this effect diminishes with greater public transportation availability. We estimate that when public transportation capacity falls below 6,500 seats per capita per kilometre, case numbers rise. Thus, robust public transportation systems may help limit the spread of airborne viruses, while inadequate systems could exacerbate transmission.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-02DOI: 10.1016/j.cstp.2024.101319
The COVID-19 pandemic has had a significant impact on the world of work. With growing support and preference revelation from both employees and employers, we might anticipate a settling in of working from home around one to two days a week, varying by occupation depending on the ability to work remotely. Although there are a growing number of studies that have analysed data collected at a point in time or over time during the pandemic, there is now sufficient time and data to treat the waves of collected data as a repeated cross section that is jointly modelled to assess systematically, the changing roles of various influences on the proportion of working days that are worked from home. This paper estimates random effects regression models for the Greater Sydney Metropolitan Area and South-East Queensland over four waves of data collected in 2020 and 2021, where this last one represents a period with almost full vaccinations and minimum restrictions (i.e., ‘new normal’). By jointly estimating four waves of data within a single modelling framework, we are able to track the changing roles of the influences found to be statistically significant across the waves. The elasticity outputs reveal how these influences impact on the propensity to WFH, giving clues on whether we were starting to see a stabilisation of WFH activity mid-way in the pandemic period that can be reflective of a ‘new normal’. Results are very supportive of employees’ preferences, suggesting that those that feel the same or more productive when working from home relative to going to the office, are more likely to working from home relative to those that feel less productive.
{"title":"COVID-19 and its influence on the propensity to work from home between March 2020 and June 2021","authors":"","doi":"10.1016/j.cstp.2024.101319","DOIUrl":"10.1016/j.cstp.2024.101319","url":null,"abstract":"<div><div>The COVID-19 pandemic has had a significant impact on the world of work. With growing support and preference revelation from both employees and employers, we might anticipate a settling in of working from home around one to two days a week, varying by occupation depending on the ability to work remotely. Although there are a growing number of studies that have analysed data collected at a point in time or over time during the pandemic, there is now sufficient time and data to treat the waves of collected data as a repeated cross section that is jointly modelled to assess systematically, the changing roles of various influences on the proportion of working days that are worked from home. This paper estimates random effects regression models for the Greater Sydney Metropolitan Area and South-East Queensland over four waves of data collected in 2020 and 2021, where this last one represents a period with almost full vaccinations and minimum restrictions (i.e., ‘new normal’). By jointly estimating four waves of data within a single modelling framework, we are able to track the changing roles of the influences found to be statistically significant across the waves. The elasticity outputs reveal how these influences impact on the propensity to WFH, giving clues on whether we were starting to see a stabilisation of WFH activity mid-way in the pandemic period that can be reflective of a ‘new normal’. Results are very supportive of employees’ preferences, suggesting that those that feel the same or more productive when working from home relative to going to the office, are more likely to working from home relative to those that feel less productive.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-29DOI: 10.1016/j.cstp.2024.101312
Passenger delays are considered as global issues that influence the overall efficiency of an airport and competitiveness as well as restricting terminal developments. This paper studied Kuwait International Airport Terminal 4 (T4); a new expansion of the old airport. This study mainly aims to analyze the influence of the design on passenger flow in T4 and how it affected the capacity in addition to obtain a path for the passenger movement from the terminal entrance until they reach the gate of the aircraft and vice versa through CAST simulation model. The effect of the T4 design on the overall efficiency was found, the current flow conditions were analyzed and compared with the required Level of Service (LOS) and several developments and expansions were suggested. Passengers flow was studied to improve passenger experience, increase operational efficiencies, maximize retail revenues and increase security effectiveness. It was indicated that customs and security facilities require expansion in areas during peak hours to maintain a high level of performance. However, the check in premium showed the minimum gap between queue capacity and the declared queuing size indicating the high level of service in this area. The results revealed that immigration queueing requires expansion. Moreover, queuing area provision indicates no capacity issues to cope with maximum queue size. The provision of immigration counters according showed no adequate queuing space to cope with MQS. It is recommended to increase the number of economy check-in counters.
{"title":"Simulation modeling of passengers flow at airport terminals to reduce delay and enhance level of service","authors":"","doi":"10.1016/j.cstp.2024.101312","DOIUrl":"10.1016/j.cstp.2024.101312","url":null,"abstract":"<div><div>Passenger delays are considered as global issues that influence the overall efficiency of an airport and competitiveness as well as restricting terminal developments. This paper studied Kuwait International Airport Terminal 4 (T4); a new expansion of the old airport. This study mainly aims to analyze the influence of the design on passenger flow in T4 and how it affected the capacity in addition to obtain a path for the passenger movement from the terminal entrance until they reach the gate of the aircraft and vice versa through CAST simulation model. The effect of the T4 design on the overall efficiency was found, the current flow conditions were analyzed and compared with the required Level of Service (LOS) and several developments and expansions were suggested. Passengers flow was studied to improve passenger experience, increase operational efficiencies, maximize retail revenues and increase security effectiveness. It was indicated that customs and security facilities require expansion in areas during peak hours to maintain a high level of performance. However, the check in premium showed the minimum gap between queue capacity and the declared queuing size indicating the high level of service in this area. The results revealed that immigration queueing requires expansion. Moreover, queuing area provision indicates no capacity issues to cope with maximum queue size. The provision of immigration counters according showed no adequate queuing space to cope with MQS. It is recommended to increase the number of economy check-in counters.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-29DOI: 10.1016/j.cstp.2024.101316
The objective of the study is to propose a methodology for optimization of Transport Sustainability Index (TSI) of National Capital Territory (NCT) of Delhi since maximum value of TSI i.e. 1.0 will occur when all the sustainability indicators attain their extremum values simultaneously, which is highly improbable. TSI is estimated using 29 most appropriate transport sustainability indicators under four pillars of sustainability, viz. environmental, social, economic, and technological. Optimization of TSI involves following steps, viz. identification of three independent variables, i.e. fuel consumption (X1), registered vehicles (X2) and population (X3) which influence all the indicators, data collection in respect of indicators and influencing variables for 30-year time period (from year 2000 to 2030), evolution of regression equations between indicators and influencing variables, and formulation of TSI as a multi-variate non-linear expression in terms of influencing variables, which is used for optimization. The generalized reduced gradient non-linear programming optimization technique is used to solve for the optimum values of influencing variables (X1opt, X2opt, X3opt) as 0.0988, 0.4709 & 0.0 respectively and optimum value of TSI (TSIopt) as 0.71, which is 25% higher than the TSI of 0.59 for the year 2023–24. The knowledge of optimum value of TSI would help the city transport policy planners to allocate, only that much quantum of infrastructural and financial resources so as to reach optimum rather than extremum values, which leads to potential savings or conservation of resources. An overall notional savings of 58% has been estimated by the study.
{"title":"Optimization of transport sustainability index to conserve resources: A case study of Delhi, India","authors":"","doi":"10.1016/j.cstp.2024.101316","DOIUrl":"10.1016/j.cstp.2024.101316","url":null,"abstract":"<div><div>The objective of the study is to propose a methodology for optimization of Transport Sustainability Index (TSI) of National Capital Territory (NCT) of Delhi since maximum value of TSI i.e. 1.0 will occur when all the sustainability indicators attain their extremum values simultaneously, which is highly improbable. TSI is estimated using 29 most appropriate transport sustainability indicators under four pillars of sustainability, viz. environmental, social, economic, and technological. Optimization of TSI involves following steps, viz. identification of three independent variables, i.e. fuel consumption (X<sub>1</sub>), registered vehicles (X<sub>2</sub>) and population (X<sub>3</sub>) which influence all the indicators, data collection in respect of indicators and influencing variables for 30-year time period (from year 2000 to 2030), evolution of regression equations between indicators and influencing variables, and formulation of TSI as a multi-variate non-linear expression in terms of influencing variables, which is used for optimization. The generalized reduced gradient non-linear programming optimization technique is used to solve for the optimum values of influencing variables (X<sub>1</sub><sup>opt</sup>, X<sub>2</sub><sup>opt</sup>, X<sub>3</sub><sup>opt</sup>) as 0.0988, 0.4709 & 0.0 respectively and optimum value of TSI (TSI<sup>opt</sup>) as 0.71, which is 25% higher than the TSI of 0.59 for the year 2023–24. The knowledge of optimum value of TSI would help the city transport policy planners to allocate, only that much quantum of infrastructural and financial resources so as to reach optimum rather than extremum values, which leads to potential savings or conservation of resources. An overall notional savings of 58% has been estimated by the study.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-28DOI: 10.1016/j.cstp.2024.101313
Passengers’ willingness to pay (WTP) has become a critical factor for airlines, particularly during the current political and economic conditions that have led to a massive increase in airline ticket prices. Nevertheless, the current literature on passengers’ WTP has concentrated on economic models that address supply and demand determinants, while marketing and psychological determinants still need further investigation. Therefore, this study aims to investigate how airline service quality, perceived value, emotional attachment, and airline brand loyalty influence passengers’ WTP for airline services, and to what extent passengers’ perceptions of airline origin can moderate these effects. Data were gathered using questionnaires and were analyzed using confirmatory factor analysis (CFA), structural equation modelling (SEM), and multi-group analysis. The results revealed that airline service quality, perceived value, and brand loyalty significantly contribute to passengers’ WTP. It also proved that passengers’ biased perceptions towards national airlines can strengthen the positive effects of these variables on their WTP for national airlines and vice versa for their WTP for foreign airlines. Finally, the study presented several theoretical contributions to airline travel literature and practical implications for airline service marketers.
{"title":"The effect of airline service quality, perceived value, emotional attachment, and brand loyalty on passengers’ willingness to pay: The moderating role of airline origin","authors":"","doi":"10.1016/j.cstp.2024.101313","DOIUrl":"10.1016/j.cstp.2024.101313","url":null,"abstract":"<div><div>Passengers’ willingness to pay (WTP) has become a critical factor for airlines, particularly during the current political and economic conditions that have led to a massive increase in airline ticket prices. Nevertheless, the current literature on passengers’ WTP has concentrated on economic models that address supply and demand determinants, while marketing and psychological determinants still need further investigation. Therefore, this study aims to investigate how airline service quality, perceived value, emotional attachment, and airline brand loyalty influence passengers’ WTP for airline services, and to what extent passengers’ perceptions of airline origin can moderate these effects. Data were gathered using questionnaires and were analyzed using confirmatory factor analysis (CFA), structural equation modelling (SEM), and multi-group analysis. The results revealed that airline service quality, perceived value, and brand loyalty significantly contribute to passengers’ WTP. It also proved that passengers’ biased perceptions towards national airlines can strengthen the positive effects of these variables on their WTP for national airlines and vice versa for their WTP for foreign airlines. Finally, the study presented several theoretical contributions to airline travel literature and practical implications for airline service marketers.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142561197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-23DOI: 10.1016/j.cstp.2024.101309
The surge in electric vehicles adoption necessitates understanding the impact of policy interventions on public electric vehicle charging infrastructure in urban areas. This research investigates the influence of pricing frameworks on the usage of public charging facilities by analyzing both behavioral and spatial attributes of these infrastructures. Utilizing open data from Palo Alto, United States, this study employs descriptive statistical methods and interpretable machine learning approaches to scrutinize the relationship between policy initiatives and charging behaviors. The analysis underscores the significance of spatial attributes on charging behaviors. Policy interventions yield noticeable alterations in charging metrics, with locations near commercial hubs showing higher utilization, while local and frequent users resist fee adjustments. The research emphasizes the necessity for customized strategies to optimize infrastructure development and management, offering a framework for policymakers and stakeholders in sustainable urban transportation. Future research should explore similar interventions in diverse urban settings using real-time data and advanced optimization techniques to better tailor policies to the unique characteristics of specific facilities.
{"title":"Policy interventions and urban characteristics in modeling electric vehicle charging infrastructure utilization","authors":"","doi":"10.1016/j.cstp.2024.101309","DOIUrl":"10.1016/j.cstp.2024.101309","url":null,"abstract":"<div><div>The surge in electric vehicles adoption necessitates understanding the impact of policy interventions on public electric vehicle charging infrastructure in urban areas. This research investigates the influence of pricing frameworks on the usage of public charging facilities by analyzing both behavioral and spatial attributes of these infrastructures. Utilizing open data from Palo Alto, United States, this study employs descriptive statistical methods and interpretable machine learning approaches to scrutinize the relationship between policy initiatives and charging behaviors. The analysis underscores the significance of spatial attributes on charging behaviors. Policy interventions yield noticeable alterations in charging metrics, with locations near commercial hubs showing higher utilization, while local and frequent users resist fee adjustments. The research emphasizes the necessity for customized strategies to optimize infrastructure development and management, offering a framework for policymakers and stakeholders in sustainable urban transportation. Future research should explore similar interventions in diverse urban settings using real-time data and advanced optimization techniques to better tailor policies to the unique characteristics of specific facilities.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-23DOI: 10.1016/j.cstp.2024.101311
This article examines the experiences of female conductors in the public transport sector, particularly the parastatal, Zimbabwe United Passenger Company (ZUPCO) regarding gender equality and women empowerment using the case of Gweru town. It employs the concept of women empowerment as its analytical framework and is based on qualitative research methods involving in-depth interviews with 15 participants comprising female conductors and male drivers. The article argues that the implementation of gender equality policies in the public transport sector without addressing misogynistic attitudes driven by patriarchal norms endangers women rather than empowering them. It found that ZUPCO female conductors experienced humiliating informal initiation into the job, negative labelling, inability to reconcile work and family and sexual abuse and harassment, which undermined the noble goal of enhancing gender equality in the public transport sector. Regardless of these negative effects, female conductors also enjoyed some degree of empowerment through employment and monetary gain, which gave them economic independence. The article concludes that the negative outcomes of embracing gender equality through women’s employment in the public transport sector outweighed the benefits.
{"title":"When embracing gender equality endangers women: Experiences of public transport female conductors in Gweru Town, Zimbabwe","authors":"","doi":"10.1016/j.cstp.2024.101311","DOIUrl":"10.1016/j.cstp.2024.101311","url":null,"abstract":"<div><div>This article examines the experiences of female conductors in the public transport sector, particularly the parastatal, Zimbabwe United Passenger Company (ZUPCO) regarding gender equality and women empowerment using the case of Gweru town. It employs the concept of women empowerment as its analytical framework and is based on qualitative research methods involving in-depth interviews with 15 participants comprising female conductors and male drivers. The article argues that the implementation of gender equality policies in the public transport sector without addressing misogynistic attitudes driven by patriarchal norms endangers women rather than empowering them. It found that ZUPCO female conductors experienced humiliating informal initiation into the job, negative labelling, inability to reconcile work and family and sexual abuse and harassment, which undermined the noble goal of enhancing gender equality in the public transport sector. Regardless of these negative effects, female conductors also enjoyed some degree of empowerment through employment and monetary gain, which gave them economic independence. The article concludes that the negative outcomes of embracing gender equality through women’s employment in the public transport sector outweighed the benefits.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-22DOI: 10.1016/j.cstp.2024.101310
Upon arrival at ports, selecting the appropriate anchorage is a critical concern shared by ship captains and port managers. This study aims to exploit the rich geographic and semantic information embedded in historical ship trajectory data to construct a micro-network of port elements and employ network analysis techniques to mine spatial service relationships among port elements, thereby establishing an Anchorage Selection Decision Support (ASDS) model. This process involves extracting vessels’ dwell location information within ports from trajectory data and using this information and its sequence to establish an Anchorages-Berths Micro-Network (ABMN) in port. By applying association rule mining techniques, this research reveals the spatial service relationships within the micro-network between anchorages and berths, and integrates relevant indicators to develop the ASDS model. The aim is to help pilots of approaching vessels in making more rational anchorage choices, thus optimizing the operational efficiency of vessels in ports. The effectiveness of this approach has been validated through experiments conducted in the research region at the Nanjing port of the Yangtze River. This research is significant for exploring the correlation between port anchorages and berths, as well as for selecting appropriate anchorages for vessels arriving at the port.
{"title":"A micro-network within the port for vessel anchorage selection decision support","authors":"","doi":"10.1016/j.cstp.2024.101310","DOIUrl":"10.1016/j.cstp.2024.101310","url":null,"abstract":"<div><div>Upon arrival at ports, selecting the appropriate anchorage is a critical concern shared by ship captains and port managers. This study aims to exploit the rich geographic and semantic information embedded in historical ship trajectory data to construct a micro-network of port elements and employ network analysis techniques to mine spatial service relationships among port elements, thereby establishing an Anchorage Selection Decision Support (ASDS) model. This process involves extracting vessels’ dwell location information within ports from trajectory data and using this information and its sequence to establish an Anchorages-Berths Micro-Network (ABMN) in port. By applying association rule mining techniques, this research reveals the spatial service relationships within the micro-network between anchorages and berths, and integrates relevant indicators to develop the ASDS model. The aim is to help pilots of approaching vessels in making more rational anchorage choices, thus optimizing the operational efficiency of vessels in ports. The effectiveness of this approach has been validated through experiments conducted in the research region at the Nanjing port of the Yangtze River. This research is significant for exploring the correlation between port anchorages and berths, as well as for selecting appropriate anchorages for vessels arriving at the port.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-15DOI: 10.1016/j.cstp.2024.101305
The COVID-19 pandemic emerged as a very influential occurrence with a profound impact on a global scale. The onset of the pandemic abruptly disrupted the regular course of everyday activities, primarily impacting urban regions. Hence, it is imperative to understand the effects of the COVID-19 pandemic on modern urban areas. This study seeks to analyze the effect of the pandemic on travel behavior by utilizing GPS data obtained from taxis, with a specific focus on spatial socioeconomic features. The M2 metro line in Istanbul has been selected for evaluation. In this analysis, four distinct periods are considered: total, off-peak, morning, and evening peaks. The stations are categorized using K-means clustering. The estimation models are constructed using ordinary least squares (OLS), spatial autoregression (SAR), and geographically weighted regression (GWR) techniques, which are applied to the variation in daily average cab trips and the characteristics of stations. The GWR models provide superior performance in comparison to the other two models, with notable distinctions observed in peak times, particularly morning peak when compared to total and off-peak counts. The findings indicate that factors such as population, population density, socioeconomic status, and the quantity of shopping malls are influential variables in elucidating and forecasting the fluctuations in taxi trip counts.
COVID-19 大流行是一次极具影响力的事件，在全球范围内产生了深远的影响。大流行病的爆发突然打乱了日常活动的正常进程，主要影响到城市地区。因此，了解 COVID-19 大流行对现代城市地区的影响势在必行。本研究试图利用从出租车上获取的 GPS 数据分析大流行病对出行行为的影响，并特别关注空间社会经济特征。伊斯坦布尔的 M2 地铁线被选作评估对象。在分析中，考虑了四个不同的时段：总高峰、非高峰、早高峰和晚高峰。车站采用 K 均值聚类法进行分类。利用普通最小二乘法（OLS）、空间自回归（SAR）和地理加权回归（GWR）技术构建了估算模型，并将其应用于日均出租车出行量的变化和车站的特征。与其他两种模型相比，地理加权回归模型具有更优越的性能，在高峰时段，特别是早高峰与总计数和非高峰计数相比，观察到明显的差异。研究结果表明，人口、人口密度、社会经济地位和购物中心数量等因素是阐明和预测出租车出行次数波动的影响变量。
{"title":"Towards socially equitable public transport systems: The effect of COVID-19 on taxi trip behavior","authors":"","doi":"10.1016/j.cstp.2024.101305","DOIUrl":"10.1016/j.cstp.2024.101305","url":null,"abstract":"<div><div>The COVID-19 pandemic emerged as a very influential occurrence with a profound impact on a global scale. The onset of the pandemic abruptly disrupted the regular course of everyday activities, primarily impacting urban regions. Hence, it is imperative to understand the effects of the COVID-19 pandemic on modern urban areas. This study seeks to analyze the effect of the pandemic on travel behavior by utilizing GPS data obtained from taxis, with a specific focus on spatial socioeconomic features. The M2 metro line in Istanbul has been selected for evaluation. In this analysis, four distinct periods are considered: total, off-peak, morning, and evening peaks. The stations are categorized using K-means clustering. The estimation models are constructed using ordinary least squares (OLS), spatial autoregression (SAR), and geographically weighted regression (GWR) techniques, which are applied to the variation in daily average cab trips and the characteristics of stations. The GWR models provide superior performance in comparison to the other two models, with notable distinctions observed in peak times, particularly morning peak when compared to total and off-peak counts. The findings indicate that factors such as population, population density, socioeconomic status, and the quantity of shopping malls are influential variables in elucidating and forecasting the fluctuations in taxi trip counts.</div></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-14DOI: 10.1016/j.cstp.2024.101307
This research delves into the determinants affecting Taiwanese college students’ purchasing behavior towards two-wheeled electric vehicles (ETWVs) and the financial allocation they are willing to commit. A choice experiment design was utilized, with a sample of approximately 900 college students, regular users of two-wheeled gasoline vehicles (TWGs). The students engaged in one of two choice scenarios, presented with general characteristics, operational efficiency, vehicle cost, and subsidy strategies. Subsequent to the scenarios, respondents indicated their willingness to pay (WTP) for a ETWV. ETWVs, apart from being an emerging transportation alternative, also present potential environmental and health benefits due to reduced air pollution. The dependent inverse hyperbolic sine (IHS) double-hurdle model was employed, facilitating the accommodation of heteroscedasticity and correlated normality. The outcomes suggest that purchasing behavior for ETWVs among college students is shaped by factors such as purchase subsidy, tax breaks, and ETWVs’ capability in supporting students’ external travel requirements. The average WTP for ETWVs among this demographic stands at US$ 1,410. Importantly, the dependent IHS double-hurdle model, considering heteroscedasticity, proved statistically superior to its counterparts. Insights from this research offer crucial information on the price range students are likely to accommodate for ETWVs and provide a foundation for framing incentive-driven policies to amplify ETWV adoption.
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