Taxi Fares Research Articles

Spatial Pattern and Driving Mechanism of Urban Taxi Fares in China

Taxi fare is related to the daily life of residents. Reasonable taxi fare not only meets the travel demand of residents but also improves the income of drivers and promotes employment. The spatial variation of taxi fares exists between different regions and cities. Previous studies on taxi fares have been conducted mostly in individual cities, and there has been no study on the spatial differentiation pattern of taxi fares on a national scale. Taking 336 cities across China as the research object, a multiple linear regression model of taxi fares was established by demonstrating the spatial variation pattern of taxi fares, the global differentiation index, spatial autocorrelation analysis, and kernel density analysis, etc. The significance of the study is to explore the law of spatial differentiation of taxi fares in China and to provide a stenographic record of taxi fare adjustment. The results show that: (1) the spatial variation of taxi fares across the country is significant, with the starting taxi fare range being between RMB 4 and RMB 14. (2) The global differentiation index of taxi fares is large, with two low-low clusters and three high-high clusters appearing spatially, and the results of the kernel density analysis surface a dispersion distribution centered on provincial capitals. (3) The divergence pattern of taxis nationwide is influenced by several factors. A multiple linear regression model is selected to establish a multiple linear regression model of urban disposable income per capita, regional GDP, urbanization rate, and urban population density, which shows that urban disposable income per capita has the greatest influence on taxi fares. The model shows that urban disposable income per capita has the greatest influence on taxi fares, and the fare of a 5 km taxi ride is 6.07. Taxi fares have a clear pattern of spatial differentiation in China and are most affected by urban disposable income per capita. Through this study, we can gain a deeper understanding of the variation in taxi fares across the country and provide data and theoretical support for the rationality of taxi fare adjustments.

ANALISA PENGARUH KENAIKAN TARIF, KEMUDAHAN, CITRA MEREK TERHADAP MINAT BERKENDARA OJEK ONLINE

This research aims to see the effect of increasing online motorcycle taxi rates which have been determined based on the Decree of the Minister of Transportation Number KP 667 of 2022. This research method was carried out quantitatively with primary data by distributing questionnaires to students in the Jabodetabek area. The variables in this research are price, brand image and ease of using the online motorcycle taxi application. The data collection method in this research uses descriptive and comparative methods. This research resulted in the conclusion that online motorbike taxi fares and brand image do not influence the interest in driving using online motorbike taxis among students, but the ease of use of the application influences the interest in driving using online motorbike taxis among students.

Navigating the roads of corporate strategy: An in-depth analysis of mobile taxi industry from the customers’ lens

This study aims to identify passenger preferences for mobile app based taxi services in Dehradun, India, to ensure sustainable business growth. The Indian taxi industry is expected to reach USD38.90 billion by 2028, growing at a compound annual growth rate (CAGR) of 13.55% from its projected value of USD20.61 billion in 2023 (Mordor Intelligence, 2023). A structured questionnaire with 28 attributes was employed in a cross-sectional survey of 384 purposively selected respondents who have used Uber and Ola at least three times. Importance–performance analysis (IPA) was utilized for data analysis. IPA identifies improvement opportunities, guides strategic planning, and assesses a firm’s competitive position in the market (Hawes & Rao, 1985; Martilla & James, 1977; Myers, 1999). The study found mobile app-based taxi services in Dehradun excelled in areas like app usability, availability of vehicles, precise locations, quick response time, multiple payment options, and the ability to call the driver through the app. The study also found that the drivers’ communication skills, map familiarity, smooth driving, and passengers’ security during the trip were satisfactory. However, the study recommends improvements in the availability and waiting time of the vehicles during odd hours, variation in taxi fares, drivers’ cancellation of rides, and availability of discounts.

Taxi fare prediction based on multiple machine learning models

The use of taxis as a fundamental mode of transportation in everyday life has led to the increased popularity of various ride-hailing applications such as Uber and Lyft, enabling users to conveniently request and view the predicted fare for their desired destination. Accurately predicting the fare is thus of significant importance. In this study, machine learning models were employed to forecast taxi fares based on factors such as distance and passenger count. As the initial data only contained latitude and longitude values, the Haversine formula was utilized to calculate the distance between two locations. Moreover, the raw data was plagued with inconsistencies such as negative fares and grossly exaggerated distances, which were resolved by implementing four data cleaning criteria. Following the preprocessing stage, three distinct models (i.e., linear regression, decision tree, and random forest) were trained and evaluated using the root mean square error metric. The results indicated that the random forest model produced the smallest error (1.264), followed by the decision tree model with a similar error rate (1.277), and lastly, the linear regression model with the highest error (1.718). Thus, the random forest model demonstrated superior performance and is recommended for accurate fare predictions.

Estimating Travel Choice Probability of Link-Based Congestion Charging Scheme for Car Commuter Trips in Jakarta

The likely effects on car commuters of enforcing congestion charging using the link-based corridor method include that they may shift to public transport, divert their route of travel, or decide not to travel to the related area. However, most recent research has focused mainly on the choice of modes. This paper examined the travel choices of private car commuters resulting from the congestion charging scheme set to be implemented in Jakarta, Indonesia. The scheme is intended to replace the current odd-even strategy. It is imperative to study all possible mutually exclusive alternatives faced by car commuters. A web-based e-survey was used for data collection, employing the stated preference method. The discrete choice multinomial logit model was chosen to analyze the data. A total of 401 of the 2125 respondents to the e-survey questionnaire link, evenly distributed to all areas of Greater Jakarta, were sampled in this study. The sample respondents who traveled by car, passing through the eight designated corridors, were analyzed. NLOGIT6 software was used to analyze the parameter of attributes, the probability of alternatives chosen, and the marginal effects of congestion charging on such corridors, employing the multinomial logit model (MNLM). One surprising finding was that the load factor and taxi fares were not significant, indicating that the level of in-vehicle overcrowding is not a concern of respondents, and taxi services are not a substitute for car travel. Another surprising finding was that income variables and job type do not significantly influence travel behavior. In terms of the probability of commuters to continue to travel by car when link-based congestion charging is imposed, only around half of the car travelers were willing to pay the congestion levy and pass through congestion charging corridors. The probability of car travelers diverting onto alternative roads is high, i.e., around 16.82% to 22.88%, while the probability of car travelers shifting to mass transportation is 17.69%. When interpreting direct marginal effects, there is a change in the probability of all travelers choosing to use private cars through the congestion charging corridor of −0.0338, or a decrease of −3.38% for every IDR 1000 increase in the congestion charging levy rate, ceteris paribus.

Urban Taxi Slogans: The People's Arts

Urban Taxi Slogans: The People's Arts

Intelligent Taxi Dispatch System for Advance Reservations

This research proposes and tests a new taxi dispatch policy to improve the existing systems used by taxi companies in Singapore. The proposed method chains trips made by reservations at least 30 minutes before the customer pick-up times. In this paper, the taxi dispatching system, Singapore Taxi Advance Reservation (STAR), is defined. A novel trip-chaining strategy based on a customized algorithm of Pickup and Delivery Problem with Time Window (PDPTW) is proposed. The idea is to chain several taxi trips with demand time points that are spread out within a reasonable period of time and with each pick-up point in close proximity to the previous drop-off location. The strategy proposed has the potential to lower the taxi reservation fee in Singapore to encourage advance reservations that facilitate trip chaining, which translates to lower taxi fares for customers, higher revenue for taxi drivers, and lower fleet ownership cost for taxi companies.

What cities have is how people travel: Conceptualizing a data-mining-driven modal split framework

As city-level modal splits are outcomes of city functions, it is essential to understand whether and how city attributes affect modal splits to derive a modal shift toward low-emission travel modes and sustainable mobility in cities. This study elucidates this relationship between modal splits and city attributes in 46 cities worldwide, proposing a two-step data mining framework. First, using the K-Means method, we classify cities into private-vehicle-, public-transit-, and bicycle-dominant groups based on their modal splits. Second, we categorize city attributes into environmental, socio-demographic, and transportation planning factors and quantify their interlocked impacts on cities' modal splits via the decision tree method. We observe that the socio-demographic factor has the highest impact on determining the cities' modal splits. In addition, high population density and employment rate are positively associated with low-emission travel modes. High gasoline tax and low public transit and taxi fares often make people reconsider possessing private vehicles. On the other hand, extreme weather conditions (e.g., hot temperatures) can prevent bicycle usage. Our contribution expands the impact of introduced city planning and policies for modal shifts toward a real-world paradigm and we present implications of the proposed framework in developing practical modal shift strategies.

Covid-19 and Precarity in South Africa’s Minibus Taxi Industry

This article considers covid-19 and precarity in South Africa’s minibus taxi industry. Covid-19 and the resulting national lockdown interrupted the operations of the industry (like other businesses) in South Africa. During the lockdown (from level 5 to level 1), some taxi operators complained that the lockdown resulted in them losing profit. Taxi drivers also complained that they are making less money through taxi fares (noting that each day they give collected fares to taxi owners and keep some of the money for petrol). The labour inspectors of the Department of Employment and Labour (DOEL) continue to find it difficult to exercise their role of inspecting working conditions in the industry. Despite the fact that the DOEL issued a Sectoral Determination for the taxi industry (Basic Condition of Employment Act 95 of 1997, Sectoral Determination 11: Taxi Sector 2005), which specifies basic employment conditions, the industry is still predominantly informal and employees have no job protection. Taxi drivers remain exempt from job-related benefits such as the Unemployment Insurance Fund (UIF), which makes it impossible for them to benefit during difficult times such as Covid-19 and unemployment. Therefore, the virus and the lockdown revealed further the precariousness of taxi drivers and the concerns around making profit by taxi owners.

Exploring ride-hailing fares: an empirical analysis of the case of Madrid

Ride-hailing is an emerging service that is transforming door to door mobility in urban areas. Users can easily request a ride through a smartphone app that informs them of the pickup time, the location of the vehicle, and the fare that they will pay in advance. Even though it is well known that Uber implements a dynamic pricing approach depending mostly on supply, demand and competition with other services, there is still little empirical evidence on the main drivers explaining the fare strategy of the company. However, a deeper understanding of prices is essential to evaluate and establish a future scenario with smarter regulation and fairer competition between ridesourcing and taxi services. Using 10-month data from the Uber’s application programming interface in the city of Madrid, this research studies the association of Uber fares with different explanatory variables. It also explores the main differences between Uber and taxi fares. The results indicate that trip distance, trip delay, day of the week, origin and destination of the trip, and rain precipitation have a statistically significant impact on Uber fares. The findings also show that on average, Uber fares are lower than taxi fares, with the exception of particular hours of the day, as well as Uber fares slightly increased during taxi strikes recently happened in Madrid. The paper concludes with some policy recommendations and insigths regarding the future of the hailing sector and the importance of prices in evaluating future changes and possibilities.

The Value of Coordination in One-Way Mobility-on-Demand Systems

In a one-way mobility-on-demand system or distributed transportation system, customer requests for rides are served by a fleet of agents, e.g., taxis or even autonomous vehicles. We present a simplified three-node network model of such a transportation system in an urban agglomeration. The agents in this model play a non-cooperative game as each one tries to maximize their individual expected profit. We compute Nash equilibria in this game for different customer load cases, specifically the light- and heavy-load cases, and compare the social cost of a system with selfish agents to that of a system with coordinated agents. In particular, we establish a lower bound for the price of anarchy as a function of the system parameters, including taxi fares. We investigate the required mechanism design in the form of the fare ratio for a downtown core node and a city outskirts node that minimizes the social cost caused by selfish agents. Furthermore, we show that this optimal fare ratio is required to bring the social cost for the selfish agents as close as possible to that of the coordinated fleet. The chosen level of abstraction for the network with only three nodes is not intended to accomplish completeness; rather, it provides elementary insights into why mobility-on-demand systems with selfish agents in many cities operate at a sub-optimal level of performance. This paper motivates the investigation of the value of coordination in more complex systems, as well as the study and implementation of coordinated one-way mobility-on-demand transportation systems.

Taxi Tipping in New York City (2014-2017): Reciprocity in Hailed vs. Dispatched Cab Fares

The present study evaluated the extent to which reciprocity (equity) theory could explain differential levels of tipping in New York taxi fares. From 2014 to 2017, the database recorded 73 million cab fares; however, only credit transactions (i.e., recording patrons’ tips) were included (28 million fares). Based on a reciprocity hypothesis, patrons in cabs hailed randomly off the street were expected to tip more compared to patrons who arranged travel at a dispatch centre. An analysis of covariance for each of the four years supported this, wherein patrons in hailed cabs tipped twice the percentage (14%) than patrons in dispatched cabs (7%); these results were confirmed using equivalent procedures that assumed neither normality nor variance homogeneity. Several limitations are discussed, as are directions for future research. Keywords: reciprocity, tipping, equity, genuine intention, taxi

EVALUATING THE COMPETITION EFFECTS OF UBER’S ENTRY INTO THE BRAZILIAN INCUMBENT CAB-HAILING APP SEGMENT

Abstract This paper assesses the competition effects of Uber’s entry into the incumbent cab-hailing app segment in Brazil. Using a monthly panel data set (from 2014 to 2016) covering the Brazilian municipalities and a difference-in-differences estimator, we show that Uber’s entry into the market resulted in an average reduction of 56.8 percent in the number of rides from cab-hailing apps in the cities where the platform operates. The magnitude of this effect suggests that Uber has had a clearly disruptive effect on the incumbent sector. We also found significant spatial heterogeneity in the competition effects of the platform when comparing the markets of the capitals of the North and Northeast regions (where Uber entered late) with the capitals of the South, Southeast, and Central West regions (where Uber entered early). Only in the second group of municipalities, we found that Uber’s entry caused a reduction in taxi fares (reduction of 12.1 percent). This indicates that the cab-hailing app sector reacted to Uber’s entry by offering discounts in fares after a longer period of exposure to a competitive environment.

Improving equity of urban transit systems with the adoption of origin-destination based taxi fares

In this paper an original approach for setting taxi fares is proposed. The approach is based on origin-destination fares and aims to increase the equity of transportation supply in an urban area: routes in certain urban areas can be very well served while others may be served poorly or not at all. Yet most citizens contribute indirectly to transit systems that are often subsidized to a considerable extent by public money. The proposed method seeks to balance this asymmetry, reducing taxi fares on origin-destination pairs that are poorly served by other transportation modes. An optimisation problem based on this principle is formulated and solved. The proposed approach is tested on a small test network and on a real-scale network. Numerical results show that the approach is applicable and useful to enhance equity in transit services.

A tool to aid redesign of flexible transport services to increase efficiency in rural transport service provision

ABSTRACTRural areas generally have lower and more dispersed demands for travel which cannot sustain conventional public transport services and consequently have a greater number of flexible and demand responsive transport services operating. These services usually operate on a stand-alone basis, are often subsidized and are typically only accessible by certain passenger types or for specific trip purposes. This generally results in uncoordinated and inefficient transport provision overall. The Flexible integrated transport services (FITS) system featured in this paper has been designed to address this problem. FITS can be used as a planning tool to assess potential benefits from relaxing operating constraints (e.g., a service's operating boundaries), which can potentially suggest service redesign. It also includes the capacity to assign subsidy payments on a trip by trip basis to increase cost efficiency whilst meeting a greater proportion of transport needs. The case study in the paper focusses on transport to health in the Aberdeenshire and Morayshire areas of Scotland in the UK. Despite flexible transport operators receiving public funds to meet passenger needs, this is currently being supplemented by public bodies paying large amounts in taxi fares in instances where there is a statutory obligation to provide travel but where no other suitable transport service exists. The results demonstrate the potential substantial savings which could be realized by allowing transport operators to redesign their services by relaxing constraints and by the reassignment of subsidies: resulting in more passenger demands being met and a reduction in public spending on taxi fares.

Challenges and Reconstruction of Competition Policy in Taxi Market Resulting from APP

The majority of regulatory authorities in the world prohibit free access to taxi market and free bargaining for taxi fares between drivers and passengers. This kind of policy restricting competition results from the game between interests groups, but also matches with significant information asymmetry in taxi market. APP remodels information transmission and trade competition mechanisms in taxi market, overturns the legitimacy foundation of restricting competition policy, and makes taxi market policy pattern with global convergence fall apart. A triangle analytical framework, so called group games-institutional environment-economic thoughts, as the important means for studying the transition of competition policy, can be used to reveal the general reasons for the transition of market regulation policy between competition openness and competition ban, and indicates that taxi markets in different law domains will achieve competition liberalization asynchronously and converge constantly to regulation policy encouraging competition.

The shared-taxi problem: Formulation and solution methods

With the rising fuel costs, ride sharing is becoming a common mode of transportation. Sharing taxis which has been prominent in several developing countries is also becoming common in several cities around the world. Sharing taxis presents several advantages as it minimizes vacant seats in cars thus reducing costs on taxi operators which results in significantly lower taxi fares for passengers. Besides the economical advantages, taxi sharing is highly important for reducing congestion on the roads and for minimizing the impact of transportation on the environment. In this paper, we formulate the problem of assigning passengers to taxis and computing the optimal routes of taxis as a mixed integer program. To solve the proposed model, we present a Lagrangian decomposition approach which exploits the structure of the problem leading to smaller problems that are solved separately. Furthermore, we propose two heuristics that are used to obtain good quality feasible solutions. The Lagrangian approach along with the heuristics are implemented and compared to solving the full problem using CPLEX. The computational results indicate the efficiency of the methodology in providing tighter bounds than CPLEX in shorter computational time.

Jobs, food, taxis and journals: Complexities of implementing Stepping Stones and Creating Futures in urban informal settlements in South Africa

This paper seeks to refocus debates on structural interventions away from ‘assessing’ their effectiveness towards understanding processes around how such interventions are implemented. Implementation Science is focused on understanding potential challenges of translating interventions from highly controlled conditions into ‘real life’ settings. Using the case study of Stepping Stones and Creating Futures a structural and behavioural intervention to reduce intimate partner violence and HIV risk behaviours amongst young women and men in urban informal settlements, we explore the challenges of implementing such an approach. We move beyond simply describing challenges of implementing, to understand how these challenges had an impact on the safe social space the intervention seeks to create as its underlying theory of change. We identify four major challenges of implementation: taxi fares, food provided during the intervention, young people’s ongoing need to work and journals provided during the intervention. We suggest that, in different ways, these factors all impinged on the emergence of a safe social space. Understanding the challenges of implementing the intervention is critical for reflecting on scaling up interventions. Central to this is the need to work with participants to help them negotiate the challenges of participating in interventions.

The economic effects of government regulation: Evidence from the New York taxicab market

This paper empirically investigates the economic effects of government regulation in a regulated taxicab market. We use a cointegration model with structural breaks to test the hypothesis that government regulation increases the price of the regulated good and/or causes the monopoly price. We examine the New York taxicab market and argue that regulation brings about artificial rents by increasing medallion prices, and an increase in medallion prices gives rises to upward pressure on taxi fares. The evidence presented shows that regulation of the New York taxicab market increases medallion prices, and this increase in medallion prices pressures on taxi fares.

Hydrogel sheet dressings and short-stretch cohesive bandaging: case study

Hard-to-heal wounds such as leg ulcers are associated with long duration and a high incidence of complications such as pain, often resulting in considerable financial burden (European Wound Management Association (EWMA), 2008). The financial burden is not just one for the NHS but for the patients as well in lost days from work, taxi fares, prescription charges and even having to take early retirement. The prevalence of venous leg ulcers is approximately 1% in the whole population and this increases with age. Where appropriate research-based treatment protocols and guidelines are in place, about 50% of leg ulcers heal within 4months (EWMA, 2008). The following case study demonstrates that using protocols, national and local guidelines can have a positive effect on the patients wound care journey and promote optimal wound care (Wounds UK, 2008).