Fare Changes Research Articles

Do Prices Grow More in Euroland? Evidence from the Airline Industry

We study annual changes in fares posted by airlines on their web sites over the period June 2002- June 2004. Using panel data techniques, annual fare changes are regressed against a set of country specific, fixed effects and control variables accounting for cost s on a specific route, inflation and exchange rate, route competitive characteristics and seasonal fixed e ffects. The estimates provide various insights on the process underlying price setting by airlines. In pa rticulars, they reveal an important relationship between airfare changes and exchange rate fluctua tions. Finally, the study suggests the presence of country effects, that do not conf orm however to the notion that airfares to Euroland destinations followed a similar trend.

The issues and challenges of a pricing system implementation

Midwest Airlines, as a medium-sized, specialty carrier operating in the midst of the highly competitive and dynamic US domestic market, must strive for both the cost efficiencies and the market competitiveness of the US majors and the new low-cost entrants. Pricing is one area where this dynamism is most noted, with huge numbers of fare and rule changes being implemented every day. Without significantly increasing staff, how can one ensure that the airline's fares are competitive in all markets? The potential for lost revenue is very large. Midwest Airlines decided that it was preferable to maintain a small, top-class pricing group but to leverage their effectiveness with advanced systems support, rather than increasing personnel, with the challenges of retaining efficiency and effectiveness that this brings. This paper describes the process, from both a business and a selection viewpoint, that was followed to implement the fare analysis control and tracking system–automated fares module (FACTS–AFM) product from SMG Technologies successfully into the Midwest Airlines pricing department. Although this process was completed nearly three years ago and applied specifically to the US market, the lessons learnt and the actions taken are just as relevant today and can also be applied to many of the international airlines still using largely manual processes.

The main determinants of the demand for public transport: a comparative analysis of England and France using shrinkage estimators

This study analyses the impacts of changes in fares, service supply, income and other factors on the demand for public transport on the basis of panels of English counties and French urban areas. The analysis is based on dynamic econometric models, so that both short- and long-run elasticities are estimated. Conventional approaches (i.e. fixed- and random-effect models) rely on the hypothesis that elasticities are the same for all areas. Having shown that this hypothesis is not valid for these data sets, the heterogeneity amongst areas is accounted for using a random-coefficients approach, and Bayesian shrinkage estimators. Estimated elasticities for France and England are compared, by using a common set of variables, similar time period and a common methodology. The results show a considerable variation in elasticities among areas within each country. The major conclusion is that public transport demand is relatively sensitive to fare changes, so that policy measures aimed at fare reduction (subsidisation) can play a substantial role in encouraging the use of public transport, thus reducing the use of private cars.

TRESIS: a transportation, land use and environmental strategy impact simulator for urban areas

The Institute of Transport Studies has developed a Transportation and Environment Strategy Impact Simulator (TRESIS) as a decision support system to assist planners to predict the impact of transport strategies and to make recommendations based on those predictions. A key focus of the simulator is the richness of policy instruments such as new public transport, new toll roads, congestion pricing, gas guzzler taxes, changing residential densities, introducing designated bus lanes, implementing fare changes, altering parking policy, introducing more flexible work practices, and the introduction of more fuel efficient vehicles. The appropriateness of mixtures of policy instruments is gauged in terms of a series of performance indicators such as impacts on greenhouse gas emissions, accessibility, equity, air quality and household consumer surplus. In this paper we introduce TRESIS to the research community, focussing on the structure of the system and the diversity of applications. Applications are presented to illustrate the diversity and richness of TRESIS as a policy advisory tool.

Bus Patronage in Great Britain: Econometric Analysis

The demand for local bus services in Great Britain was investigated to obtain estimates of fare elasticities for use in policy calculations to project the change in bus patronage nationally as a result of a given average fare change, and to explore possible variation in the elasticity. The estimation of bus fare elasticities was based on annual national and regional aggregate data for the years 1974 to 1996 on bus patronage, fares, and other relevant factors influencing bus use. The estimations used dynamic econometric models relating per capita bus patronage (all journeys) to real per capita income, real bus fares (average revenue per journey), and service level (bus vehicle kilometers). The results indicate that patronage is relatively fare-sensitive, with an elasticity for all Great Britain of −0.4 in the short run and −0.9 in the long run. The evidence suggests that the long-run values are at least twice the short-run elasticities and that the total response takes about 7 years. Indications are that full-fare passengers are less sensitive to fare changes than the average bus passenger. The strong negative relationship between automobile ownership and bus patronage in the long run is confirmed, although the short-run effect is negligible. The cross-elasticity between bus patronage and motoring costs appears to be negligible in the short run and to be about 0.3 to 0.4 in the long run.

Transit Services in a Competitive Market

Since the new Hong Kong International Airport debuted on July 6, 1998, ground trips to the airport have undergone drastic changes. A number of transit modes are provided to connect the new airport with the territory, including three major ones—Airport Express Line (AEL), Air Bus (A-bus), and External Bus (E-bus). All of these transit services are operated by profit-driven businesses, dividing the 167,000 daily trips. Currently, the Hong Kong government imposes fare control on the bus services, whereas the rail service (e.g., AEL) is exempt from such control. The fare changes resulting from this competition were examined to assess their impacts on the traveling public as well as on each operator. In addition, an evaluation was made of the impact of deregulating this policy of fare control and allowing the operators to compete freely in a noncooperative manner. Transit services in a competitive market could lead to very different outcomes. For some districts, a transit operator could increase revenue by fare increases, whereas for other districts, revenue increase could be achieved only with fare reduction. Where and why competition falls into these different operating paradigms is an interesting topic for investigation. The methodology for this analysis, as well as the results based on actual data, is discussed.

Metropolitan Atlanta Rapid Transit Authority Fare Elasticity Model

The introduction of a variety of fare media has increased riders’ choices of how to pay for transit and has provided transit agencies with the ability to price fare media differently. An aggregate elasticity value such as the Simpson-Curtin formula provides cannot capture the shifts among fare media, and elasticities for specific fare payment categories do not directly address these shifts. The Metropolitan Atlanta Rapid Transit Authority (MARTA) fare elasticity model was developed to identify shifts among fare payment methods and to forecast ridership and revenue changes resulting from a fare change. The key element in predicting shifts among fare media is the identification of the propensity of riders to choose one fare medium over another even if their prices are identical. After current ridership is adjusted to take account of these shifts, fare elasticities are then applied to predict post-fare-change ridership levels by fare payment method. The new ridership figures are used to forecast new revenue. The model requires minimal input from the user, primarily current ridership by fare payment mode and current and proposed fare levels. Elasticities can also be changed by the user to test the sensitivity of the elasticity assumptions, and factors such as the intensity of weekly and monthly TransCard use are additional input options. The model has proved to be very accurate when applied to the most recent MARTA fare change on July 1, 1995, predicting overall ridership within 0.05 percent and revenue within 0.7 percent. A model enhancement allows the user to recalibrate the model after any future fare changes by testing the accuracy of different elasticity assumptions.

Introducing Fare Simplification and New Convenience Fares at Connecticut Transit

On June 28, 1998, the New Fare Deal was implemented in Connecticut, designed to make fare payment simpler and more convenient for customers. The program applied to three divisions of Connecticut Transit (CTTRANSIT) in Hartford, New Haven, and Stamford, as well as to other state-contracted transit services in Waterbury, New Britain, Bristol, Meriden, and Wallingford. The changes include elimination of local fare zones and the introduction of new convenience fares including 1- and 7-day passes. The fare changes were implemented in response to recommendations developed in a major market research study for CTTRANSIT, reported on in 1996, to encourage ridership in CTTRANSIT’s fastestgrowing market for suburb-to-suburb travel, to respond to the welfare-towork initiative, and to utilize more fully the features of the Ticket Reading and Issuing Machine (TRIM) equipment installed in 1995. Reviewed in this paper are what changes were implemented, why the changes were implemented, and what results have occurred to date. Detailed beforeand-after ridership data are not available. However, during the first 6 months following fare simplification, passenger revenue exceeded budget by about 3 percent (or almost $300,000), demonstrating that the anticipated revenue loss did not materialize. New convenience fare media have proved to be very popular.

Issues in Fare Policy: Case of the New York Taxi Industry

Setting taxi fares is one of the most delicate and difficult tasks faced by taxi regulators. Fare setting is delicate because political forces are strong on both sides of the issue. The difficulties lie in reliably determining taxi costs and revenues and how a fare increase will affect service quality. Major issues commonly raised in connection with fare policy are considered, including the goals of fare changes, the relevance of medallion prices, and implications for service availability. It is concluded that fare increases can achieve their goal of increasing revenues to the taxi industry but that additional regulatory action is required to ensure improvements to driver and vehicle quality. Arguments that fare increases are unnecessary in the face of high medallion prices are shown to be impractical and possibly counterproductive. Finally, it is argued that fare increases expand the availability of taxi service and that availability considerations should be an integral part of fare policy.

An adaptive method for generating demand inputs to airline seat inventory control models

In order to increase the passenger load factor and total profit, most airlines offer several different fares to passengers on the same flight. Seat inventory control is the process of assigning the available number of seats to different fare classes. During the last three decades, various aspects of this problem have been considered in the literature. The basic input data for the existing airline seat inventory models are the demand distributions for seats in particular fare classes. Statistical data as a base for forecasting future passenger demand are very often not available (opening a new route, significant changes in fares, the appearance of competitive carriers, etc.). The current models are not able to handle cases where no prior historical data is available. This paper attempts to develop an approach to deal with this problem. The adaptive airline seat inventory control, which is proposed, is based on the Bayesian approach. The model developed is illustrated by numerical examples.

Infrequent Riders: One Key to New Transit Ridership and Revenue

The mass transit industry has long focused on regular riders, large numbers of trips, and daily commuting. Captive rider and transit dependency concepts are also common in the transit industry's view of its markets. However, recent research challenges these views, especially the frequency of use. Results from three sources are discussed: onboard surveys, fare structure changes, and the transit voucher (commuter check) fare subsidy plan. The findings suggest that infrequent riders are a critical transit market and perhaps the key to building transit ridership and revenues.

Infrequent Riders: One Key to New Transit Ridership and Revenue

The mass transit industry has long focused on regular riders, large numbers of trips, and daily commuting. Captive rider and transit dependency concepts are also common in the transit industry's view of its markets. However, recent research challenges these views, especially the frequency of use. Results from three sources are discussed: on-board surveys, fare structure changes, and the transit voucher (commuter check) fare subsidy plan. The findings suggest that infrequent riders are a critical transit market and perhaps the key to building transit ridership and revenues.

The impact of taxi deregulation on small urban areas: some New Zealand evidence

In 1989 the New Zealand government deregulated the taxicab industry. Barriers to entry and centralised fare setting were abandoned. This paper examines the impact of the deregulation on industry concentration and fares in urban areas with populations of less than 100 000. While there appears to be only minor changes in concentration and fares in these areas, the direction and magnitude of fare changes, in particular, appear to be related to the size of the urban centre. Two alternative explanations are offered for this result. Evidence is presented which supports one explanation and indicates that the deregulated taxi market is competitive.

Competitive fare and frequency effects in airport market share modeling

Previous efforts to model the distribution of passenger traffic between airports in a multi-airport system have focused on ‘catchment areas’ associated with competing airports, which generally do not change in the short to medium term. Since deregulation of US airline markets, however, there have been substantial shifts in airport market shares as a result of changes in relative airline fares and service frequency at competing airports serving the same metropolitan area. In this paper, we develop and estimate an airport market share model based on the dynamics of airline pricing and frequency decisions, which can in fact vary dramatically over time. We argue that the distribution of traffic between competing airports is modeled most correctly at the level of the origin-destination market, as a function of relative fares charged by airlines at each airport and the effective frequency of service in the O-D market from each airport. The statistical estimation of price and time elasticities for several case studies demonstrates the importance of including these airline supply decisions in the modeling of airport market shares.

Quantity, quality and the welfare effects of US airline deregulation

In this paper we employ a method for estimationg quality-adjusted demand to calculate measures of the change in consumer suruplus due to US airline deregulation. The quality-adjusted estimates of the price elasticity of demand indicate that consumers are from 25% to 50% more sensitive to changes in air fares than unadjusted estimates would suggest. Changes in unadjusted consumer surplus overstate the net welfare gains from deregulation by roughly a factor of two, strongly suggesting that adjustments for quallity of service are essential to welfare analysis of regulatory changes in this industry

Transit ridership, incident effects and public policy

Transit ridership and performance is significantly affected by incidents such as labor strikes, work stoppages and gasoline shortages. This paper discusses the behavioral implications of such phenomena, specifically with regard to modeling the effects of incidents on transit ridership using aggregate time-series data. Transit users may respond to incidents by changing their perceptions of transit service utility, or by changing their location and travel behavior on either a permanent or a temporary basis. It appears that sensitivity to the effects of incidents increases with the degree of transit dependence and trip discretion on the part of the individual user. The speed at which transit ridership recovers to preincident levels appears to be more directly a function of market competitiveness. Transit managers can respond to the threat of strikes through a variety of mitigation and adaptation techniques. Mitigation strategies include averting the strike, attempting to shorten it or providing replacement service during the strike. Adaptation strategies may include fare changes, service changes or changes in operating subsidies implemented in the aftermath of a particular incident. These strategies and their long- and short-term effects on ridership are discussed in the context of the transit industry in the United States.

Transit pricing research

Several decades of research on transit pricing have provided clear insights into how riders respond to price changes in both the transit and automobile sectors. For the most part, riders are insensitive to changes in either fare levels, structures, or forms of payments, though this varies considerably among user groups and operating environments. Since riders are approximately twice as sensitive to changes in travel time as they are to changes in fares, a compelling argument can be made for operating more premium quality transit services at higher prices. Such programs could be supplemented by vouchers and concessionary programs to reduce the burden of higher fares on low-income users. Also, cross-elasticity research suggests that higher automobile prices would have a significantly greater affect on ridership than lower fares. Most research on transit fare structures shows that the common practice of flat fares is highly inequitable, penalizing short-distance and off-peak users. Free fare programs have proven quite costly for each new transit user attracted and have rarely lured motorists to transit. Free fares limited to downtowns have been more successful than systemwide free fare programs. While prepayment schemes have met with success in the U.S. and Europe, honor fares have suffered from excessive revenue losses in at least one case in the U.S. Some of the more noteworthy fare policy successes in North America have been Bridgeport's combined pass-fare program, Allentown's deep discounts, Ottawa's major fare reduction and differentiation, and Columbus's substantial midday discount. As paratransit and other new transit alternatives to conventional bus continue to emerge, new, more differentiated fare practices can be expected in the future.

A study of rail demand in a two‐tier fares environment

A method based on logit analysis is suggested for predicting the effects on patronage and revenue of relative changes in peak and offpeak fares. The method also permits the ready estimation of consequent changes in service profitability. Data was collected specifically for this study from British Rail's Teesside corridor to achieve model calibration. Results show the extent to which demand in peak and offpeak fare‐periods is complementary when fare restrictions are applied only to the morning peak.

A time-series analysis of public transit ridership in Portland, Oregon, 1971–1982

This paper examines the factors affecting changes in transit ridership in Portland, Oregon, during the period 1971 through 1982. A time-series methodology is used to investigate the effects of service level, travel costs, and market size at the system, sector, and route levels. Transfer function and multiple time-series models are compared. Intervention analysis is used to determine the impact of 81 service-level changes and 5 fare changes. A comparison is made of the elasticities estimated for these changes with elasticities developed from other studies.

Incremental Optimization Design of Transit Service

An interactive design procedure for the incremental optimization of transit route service is developed based on the concept of elasticity and the total differential. The purpose of this method is to find the set of optimum fare and frequency changes that management can incrementally implement through time to achieve a certain objective under given constraints. The method is applied to a Twin Cities commuter route, illustrating the selection of the optimum set of policy changes. The transit performance map, a major product of the incremental optimization method, can provide important information about the system behavior. Using this map, the transit manager can determine the forecast optimum route performance through time as well as the optimum scheduling and pricing policies needed to reach the desired performance level. Each optimization session lasts 2-3 min on an IBM-PC.