Subjective value of time in bus transit travel

Horowitz, Alan J.

doi:10.1007/bf00165263

Cited by 34 publications

(21 citation statements)

References 4 publications

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“…A better method is magnitude estimation, the technique used in the earlier study (Horowitz, 1981). Nonetheless, some general conclusions about transfer penalties can be drawn from the average ratings presented in Table II.…”

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confidence: 95%

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Transfer penalties: Another look at transit riders' reluctance to transfer

Horowitz¹,

Zlosel²

1981

Transportation

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confidence: 95%

“…In a recent article in this journal (Horowitz, 1981), it was asserted that there are two components of transfers that affect the disutility of bus transit trips. The first component is the act of changing buses, which produces a large penalty that is independent of the amount of time involved in transferring.…”

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confidence: 99%

Transfer penalties: Another look at transit riders' reluctance to transfer

Horowitz¹,

Zlosel²

1981

Transportation

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“…Travelers' dislike for transfers is well documented (Horowitz, 1981;Horowitz and Zlosel, 1981;Stern, 1980). A dramatic simplification in the four-step process can be made if it is first assumed that choice riders do not make multiple transfers.…”

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confidence: 99%

“…Very little new calibration was done to implement the Racine network on TRFM. All but two of the model parameters were taken from previous studies in Racine and Milwaukee (Southeast Wisconsin Regional Planning Commission, 1978) or Chicago (Horowitz, 1981). Brute-force calibration was necessary to find one parameter (the in-vehicle-time weight) in the mode-split equation and to find the fraction of trips that are assumed captive.…”

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confidence: 99%

Simplifications for single-route transit-ridership forecasting models

Horowitz

1984

Transportation

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The growth in popularity of microcomputers has reemphasized the need for simplified transit-planning techniques. This paper describes and evaluates a single-route ridership forecasting model which is designed to fit within a modest-sized microcomputer. The model is based upon the traditional four-step urban transportation modeling process, but it is simplified by removing the possibility of multiple transfers and by eliminating the highway network. An analysis of model error shows that these simplifications do not appreciably affect the accuracy of the forecasts. A particular advantage of implementing the model on a microcomputer is the user-friendliness that can be achieved by employing interactive color graphics for data input.

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“…In the work presented here, we follow in the footsteps of several other researchers who have investigated the impacts of psychological factors on travel behavior by investigating the perceived assessments of travel amounts. For example, Koppelman (1981) used nonlinear utility functions to assess the increasing burden of travel time, while Horowitz (1981) used magnitude estimation, a psychological scaling technique, to relate various time elements of a bus transit trip to an automobile trip. Although these and other studies have focused on relating objective travel distances or times for specific trips or trip segments, to individuals' perceptions of those same quantities, our investigation is (to our knowledge) among the first 1 to assess individuals' qualitative perceptions of the amount of traveling they do in general terms, as a function of their actual travel and other potential explanatory variables.…”

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Exploring the Cognitive and Affective Mechanisms Behind Subjective Assessments of Travel Amounts

Ory

Mokhtarian

Collantes

2007

Environment and Behavior

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Travel demand models focus on explaining how much individuals actually travel but offer no insight into how much individuals think they travel. The authors propose that the latter is an important determinant of traveler behavior, and that actual mobility is refracted through a variety of filters that magnify or diminish those subjective evaluations of travel amounts. Linear regression models of subjective mobility measures provided by 1,358 San Francisco Bay Area commuters were estimated earlier; the focus of this article is on identifying the potential cognitive and affective mechanisms that influence subjective mobility upward or downward, after controlling for objective mobility. The authors find three major types of mechanisms: awareness-heightening, affective, and comparison-inducing. Recurring patterns of effects in these three categories are analyzed in the light of psychological and marketing research concepts including the availability heuristic, social comparison, relative deprivation, autobiographical memory, and motivation theory. policy implications if one of the two commuters answered that she traveled "a lot" for work and the other answered that he traveled "very little" for work. Would the person who said he traveled "very little" for work be as receptive to travel-reducing policies, such as telecommuting and compressed work schedules, as the person who thought she traveled a lot? KeywordsThese and similar questions motivated the current study, which explores the idea of subjective mobility. Here, subjective mobility refers to individuals' qualitative assessment of their travel amounts. It was captured by a survey instrument that asked respondents the following question (among many others) across a variety of types of travel: "How would you describe the amount of travel you do?" with a 5-point ordinal scale of response options. The goal of the current work is to discuss and investigate the factors that shape these subjective judgments, after controlling for the actual amount of travel they did.Transportation policy makers have long been aware of the importance of psychological factors in travel. In current practice, almost every travel demand model used in the United States (and elsewhere) considers waiting for a transit vehicle to be substantially more onerous than riding in a transit vehicle (it is typical for the negative coefficient of wait time in a utility function to be 2 to 3 times larger in magnitude than the coefficient of in-vehicle travel time). As a result, proposed transit alternatives that have more frequent service may be favored by demand models over faster alternatives with less frequent service. Thus, the psychological impact of waiting for a transit vehicle is directly reflected in transportation policy decision making. In the work presented here, we follow in the footsteps of several other researchers who have investigated the impacts of psychological factors on travel behavior by investigating the perceived assessments of travel amounts. For example, Koppelman (1981) used no...

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Subjective value of time in bus transit travel

Cited by 34 publications

References 4 publications

Transfer penalties: Another look at transit riders' reluctance to transfer

Transfer penalties: Another look at transit riders' reluctance to transfer

Simplifications for single-route transit-ridership forecasting models

Exploring the Cognitive and Affective Mechanisms Behind Subjective Assessments of Travel Amounts

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