Home-based telecommuting and intra-household interactions in work and non-work travel: A seemingly unrelated censored regression approach

Although telecommuting has become a popular option as a new mode of working, no theoretical or empirical consensus has been reached on its potential for substituting or generating travel. This study aims to evaluate the impact of a household head’s telecommuting on household travel while controlling for the interdependence within a household and across travel purposes, by applying seemingly unrelated censored regression models to data from the 2006 Household Travel Survey in the Seoul Metropolitan Area. In terms of vehicle kilometers traveled, the analysis shows that telecommuters’ non-commute and non-work trips as well as his/her household members’ non-work trips are greater than those of non-telecommuters and their household members’, whereas telecommuting partially reduces commuting trips. However, an analysis stratified by household type reveals that the difference for household members is significant only in households with less than one vehicle per employed member: in such households (with insufficient vehicles available), the vehicle otherwise used for mandatory travel, such as for the household head’s commute, can be used for non-commute purposes or by other household members if the household head does not use it for commuting. This implies that, when vehicle travel budgets of a given household are limited, this compensatory travel mechanism can make optimum use of limited resources (i.e., vehicles), but offsets the travel-substituting effect of telecommuting. Accordingly, to more precisely estimate the impact of telecommuting-promotion policies and apply them as part of travel demand management strategies, their counteracting effects among household members should be considered.     

Transportation impacts of center-based telecommuting: Interim findings from the Neighborhood Telecenters Project

The transportation impacts of center-based telecommuting for 24 participants (representing 69 person-days of travel and 295 trips) in the California Neighborhood Telecenters Project are analyzed. Comparing non-telecommuting (NTC) day to telecommuting (TC) day travel shows that person-trips did not change significantly, whereas vehicle-trips increased significantly (by about one trip) on TC days. Both PMT and VMT decline significantly on TC days: by an average of 68 miles (74%) and 38 miles (65%), respectively. When these savings are weighted by the frequency of telecommuting, overall reductions in PMT and VMT come to 19% and 17%, respectively, of total weekday travel. Commute trips increase slightly (by 0.5 trips) but significantly, mainly due to lunch-time trips made home from the telecenter. Total non-commute travel does not increase, but there is a significant shift from other modes to driving alone on TC days. Commute mode split on NTC days is not affected by telecommuting. Travel on TC days tends to be compressed into fewer hours. Higher numbers of return home, eat meal, shopping, and social/recreational trips are made on TC days, in exchange for a reduction (to zero) in the number of change mode trips.     

The trade-off between trips and distance traveled in analyzing the emissions impacts of center-based telecommuting

Several travel indicators were compared between telecommuting (TC) days and non-telecommuting days for a sample of 72 center-based telecommuters in California. Distance traveled decreased significantly on TC days, with average reductions of 51 person-miles (58%) and 35 vehicle-miles (53%). When weighted by telecommuting frequency, average reductions of 11.9% in PMT and 11.5% in VMT were found over a five-day work week. Person-trips and vehicle-trips increased slightly (but not significantly) on TC days. This was due to statistically significant increases in commute trips by telecommuters (who more often went home for lunch on their TC days), partly counteracted by decreases in non-commute travel. The drive-alone mode share increased on TC days, both for all trips, and for commute trips in particular. Walking and biking shares also increased modestly on TC days, whereas shares of transit and ridesharing declined. Despite the increase in trip rates, TC-day reductions were found for all pollutants analyzed: 15% for total organic gas emissions, 21% for carbon monoxide, 35% for oxides of nitrogen, and 51% for particulate matter. The reduction in VMT more than compensated for the marginal increase in number of trips (and consequently, cold starts) on telecommuting days.     

Telecommuting and urban sprawl: mitigator or inciter?

There is some evidence to the effect that as cities become increasingly congested new housing starts occur at greater distances from urban centers while jobs tend to remain center-concentrated or develop in other suburbs. In either case, mean commute distances tend to increase. Telecommuting is seen as a means of increasing the jobs-housing balance in urban and suburban areas by enhancing the ability to move work to, or closer to, the workers' residences rather than requiring workers to commute to work daily. This has the immediate side effect of decreasing automobile congestion and associated energy consumption and air pollution. There is a possible longer term adverse impact of telecommuting resulting from its ability to decrease constraints on household location, thereby enhancing the rate of spread of suburbia. This paper reviews evidence concerning the possible effects of telecommuting on urban sprawl, as derived from a two-year test of telecommuting in California, and describes two scenarios of urban form development made more feasible by telecommuting.     

The sequenced activity mobility simulator (SAMS): an integrated approach to modeling transportation, land use and air quality

The persistence of environmental problems in urban areas and the prospect of increasing congestion have precipitated a variety of new policies in the USA, with concomitant analytical and modeling requirements for transportation planning. This paper introduces the Sequenced Activity-Mobility Simulator (SAMS), a dynamic and integrated microsimulation forecasting system for transportation, land use and air quality, designed to overcome the deficiencies of conventional four-step travel demand forecasting systems. The proposed SAMS framework represents a departure from many of the conventional paradigms in travel demand forecasting. In particular, it aims at replicating the adaptative dynamics underlying transportation phenomena; explicitly incorporates the time-of-day dimension; represents human behavior based on the satisficing, as opposed to optimizing, principle; and endogenously forecasts socio-demographic, land use, vehicle fleet mix, and other variables that have traditionally been projected externally to be input into the forecasting process.     

Analyzing the preference for non-exclusive forms of telecommuting: Modeling and policy implications

This study examines three models of the individual's preference for home- and center-based telecommuting. Issues concerning the estimation of discrete models when the alternatives are non-exclusive are discussed. Two binary logit models are presented, one on the preference to telecommute from a center versus not telecommuting from a center (adjusted ² = 0.24), and the other on the preference to telecommute from a center over telecommuting from home (adjusted ² = 0.64). A nested logit model is also estimated on the following four alternatives: preferring not to telecommute, preferring either form of telecommuting, preferring to telecommute from home, and preferring to telecommute from a center (adjusted ² = 0.35).The results of the models illustrated the importance of attitudinal measures in measuring an individual's preference to telecommute. Oblique factor scores representing workplace interaction, stress, workaholism, internal control, and commute stress were statistically significant in some or all of the models. Other explanatory variables which were found to be consistently significant were education, job suitability, and age. Most respondents preferred either to telecommute from home or were indifferent between either form of telecommuting, which raises the question as to whether there really is a sizeable market niche to be filled by telecommuting centers, and hence whether they may make a significant contribution to transportation demand reduction.     

Impact of telecommuting on spatial and temporal patterns of household travel

A spatial and temporal analysis of travel diary data collected during the State of California Telecommuting Pilot Project is performed to determine the impacts of telecommuting on household travel behavior. The analysis is based on geocoded trip data where missing trips and trip attributes have been augmented to the extent possible. The results confirm the earlier finding that the Pilot Project telecommuters substantially reduced travel; on telecommuting days, the telecommuters made virtually no commute trips, reduced peak-period trips by 60%, total distance traveled by 75%, and freeway miles by 90%. The spatial analysis of the trip records has shown that the telecommuters chose non-work destinations that are closer to home; they exhibited contracted action spaces after the introduction of telecommuting. Importantly, this contraction took place on both telecommuting days and commuting days. The telecommuters distributed their trips, over the day and avoided peak-period travel on telecommuting days. Non-work trips, however, show similar patterns of temporal distribution on telecommuting days and commuting days. Non-work trips continued to be made during the lunch period and late afternoon and evening hours.     

Short-term impact analysis of fuel price policy change on travel demand in Malaysian cities

Abstract

Malaysia is one of the few countries in the world that provides a fuel subsidy to consumers. Due to the recent economic crisis, the Malaysian Government decided to revise its fuel subsidization policy from a fixed price subsidy to a floating price subsidy dependent on global oil demand. Recognizing that the change in fuel subsidization policy can have an impact on travel behavior, this article investigates the short-term impact of the policy change on private and public transportation in the Klang Valley region of Malaysia. Spectral analyses are performed to investigate if the policy change has an impact on private vehicle travel demand, measured in terms of road traffic, and short-term travel demand elasticity with respect to fuel price is estimated. To measure the impact on the public transportation system, the demand cross-elasticity values of rail transit and buses are also estimated. It was found that traffic flow reduces with an increase in fuel price, although elasticity and cross-elasticity values obtained are low. The article finds that there is a potential mode shift from private vehicles to rail transit with increasing fuel price. It is demonstrated that reducing fuel price subsidy can be an effective travel demand management strategy to alleviate congestion.     

Distributed work and travel behaviour: The dynamics of interactive agency choices between employers and employees

This paper develops a framework within which multiple agents make discrete choices in respect of a common objective – the determination of participation in distributed work, especially the opportunities and constraints associated with telecommuting. Ideas in discrete choice theory and game theory are combined to define a set of choice experiments in which employees and employers interact in arriving at a choice path in a distributed work context. A state choice experiment with offers and feedback, known as an interactive agency choice experiment (IACE), is empirically investigated in the context of telecommuting options with an exploratory sample of employees and employers in Sydney, Australia. The approach highlights the role of information and negotiation in breaking down the barriers to more flexible work activity, to deliver potential benefits to the transport system such as reduced traffic congestion and environmental sustainability. The paper identifies the types of incentives that an employee/er has to offer the employer/employee in securing effective telecommuting. This revised version was published online in June 2006 with corrections to the Cover Date.     

Developing an activity-based trip generation model for small/medium size planning agencies

The primary shortcoming of traditional four-step models is that they cannot capture derived travel demand behaviors. However, travel demand modeling (TDM) is an essential input for urban transportation planning. TDM needs to be highly precise and accurate by integrating the accurate base year estimation along with suitable alternatives. Currently, activity-based models (ABMs) have been developed mostly for large metropolitan planning organizations (MPO), whereas smaller/medium-sized MPOs typically lack these models. The main reason for this disparity in ABM development is the complexity of the models and the cost and data requirements needed. We posit however that smaller MPOs could develop ABMs from traditional travel surveys. Therefore, the specific aim of this paper is to develop a probabilistic home-based destination activity trip generation model considering travel time behavior. Results show that the developed model can significantly capture the actual number of trip generations.     

Metropolitan size and the impacts of telecommuting on personal travel

Telecommuting has been proposed by policy makers as a strategy to reduce travel and emissions. In studying the metropolitan size impact of telecommuting on personal travel, this paper addresses two questions: (1) whether telecommuting is consistently a substitute or complement to travel across different MSA sizes; and (2) whether the impact of telecommuting is higher in larger MSAs where telecommuting programs and policies have been more widely adopted. Data from the 2001 and 2009 National Household Travel Surveys are used. Through a series of tests that address two possible empirical biases, we find that telecommuting consistently had a complementary effect on one-way commute trips, daily total work trips and daily total non-work trips across different MSA sizes in both 2001 and 2009. The findings suggest that policies that promote telecommuting may indeed increase, rather than decrease, people’s travel demand, regardless of the size of the MSA. This seems to contradict what telecommuting policies are designed for. In addition, model results show that the complementary impact of telecommuting on daily travel is lower in larger MSAs, in terms of both daily total work trips and daily total non-work trips.     

A suppressed demand analysis method of the transportation disadvantaged in policy making

Abstract

This paper proposes a method for estimating transportation supply requirements when the suppressed demand of the transportation disadvantaged (TD) can be calculated and added to existing demand for travel. The underlying assumption is that the travel conditions of these TD groups must be equal to the ‘conventional’ demand, known as ‘full release’. Utilising the modelling approach for TD, suppressed demand analysis, diagnosis of difficulties and equity between conventional and disadvantaged groups were realised, while elaborating special cases for the most vulnerable TD groups (such as elderly and disabled persons) and simultaneously identifying areas of difficulty. From the early virtual results, it is concluded that, for the full release of suppressed trips (only a 5% increase), policy makers must be ready to face some financial burdens, requiring coordination of effort to both standardise these TD groups and reduce the costs incurred by operators.     

Estimating induced travel for evaluation of metropolitan highway expansion

This paper demonstrates how induced travel can be estimated for incorporation into the evaluation process for highway expansion projects, at a sketch planning level of analysis. The approach is useful especially in cases where four-step urban travel models are either unavailable or are unable to forecast the full induced demand effects. The methodology is applied to a hypothetical freeway expansion analysis. Our analysis suggests that the magnitude of travel induced by highway expansion increases significantly as a function of initial congestion levels prior to expansion. However, under even extreme scenarios of initial congestion and consequent forecasted induced travel, there is a positive impact with respect to congestion relief.     

Asking the right questions about telecommuting: Avoiding pitfalls in surveying homebased work

In designing travel behavior surveys, the problem is to define “work,” “home,” and similar words that are commonly used in our language but which have acquired a plethora of associated meanings. The difficulty has not been resolved by the many new terms coined to describe non-traditional ways to work. Such words as “telecommuting,” “teleworking,” “at-home work,” “hoteling,” “homebased business,” “road warriors” and “mobile workers,” lack any agreed-upon definitions yet they are used in common parlance as if they did. These new workstyles are of interest to travel planners because they may involve trip reduction. To forecast just how much trip reduction will occur, behavior needs to be measured by objective criteria. To avoid definitional traps, we recommend phrasing questions in terms of measurable variables such as the place of work and the time in days and hours spent at each location. That approach leaves researchers the option of applying their own definitions that fit the context of their analyses. Thus, rather than ask “How many days a week do you telecommute?” the more precise question can be asked: “How many days last week did you work at home instead of going to your usual work location?” This approach has the advantage that information gathered over years can be used unambiguously in various contexts. Definitions can be applied at the point of analysis. This paper illustrates errors and confusion that can arise from casually worded surveys using examples from private and public surveys. The author proposes a set of core questions with four levels of priority for consideration in designing future surveys of travel behavior.     

A review of the impact of parking policy measures on travel demand

This paper reviews the empirical evidence relating to the impact of parking policy measures on the demand for parking and for travel. Disaggregate modal choice models, disaggregate parking location models and site‐specific studies of parking behaviour are examined. With regard to modal choice models, it is concluded that few studies deal adequately with parking factors, but that there is some support for the view that parking policy measures are a relatively important influence on modal choice. When parking location models are examined parking policy variables are shown to have a substantial impact on choice of parking location. With regard to site‐specific studies, the paper concludes that there is a great variation in the parking price elasticities quoted, which reflects partly the methodological problems associated with such studies. Suggestions to improve model specification are made.     

Discrete mode-choice analysis of urban travel demand by the Analytic Hierarchy Process

This paper develops a new procedure for the problem of multimodal urban corridor travel demand estimation by using the Analytic Hierarchy Process (AHP). Certain conceptual and operational features of the AHP are common to the discrete choice theory-based modeling approach. Whereas the computational and data requirements of standard discrete choice models are immense, the proposed AHP approach deals efficiently with multidimensionality, nested demand structure and discrete travel decision making behavior. The paper concludes by summarizing the AHP-aided, step-by-step procedure for metropolitan travel demand (modal split) estimation.     

Travel demand estimation risk for high‐speed railway transport considering travel price competition

The Hokkaido Shinkansen (HS) bullet train line is under consideration to open in 2020. In this study, travel demand is estimated for the HS. Because some explanatory variables that are used for such estimation can have estimation errors, travel demand estimation risk is also calculated. In addition, because the HS can compete with airlines for modal share, the impacts of travel price competition (TPC) on the travel demand and the demand estimation risk are also estimated. In this study, the travel demand estimation risk is measured as the variance or the SD of the stochastic travel demand. The analysis reveals the following: the modal share of HS is 16% less when TPC is considered than when it is not considered; TPC causes the travel demand estimation risk to decrease; the probabilities of the HS operating at a deficit with and without consideration of TPC are calculated as 31.2% and 1.25%, respectively, and the increase in the mean consumer surplus accruing from the HS is calculated as JPY 47bn/year ($US588m/year) without TPC and as JPY 66bn/year ($US825m/year) with TPC. Copyright © 2012 John Wiley & Sons, Ltd.     

Interpreting employee telecommuting adoption: An economics perspective

Travel demand is derived from activities at the trip destination; therefore, media that have the potential to provide services previously only supported by transportation will have a chance to be chosen by passengers. The idea of telecommuting is considered the most promising substitute of work trips and thus a good strategy of transportation demand management. From a microeconomics perspective, demand for goods or services can be interpreted as a function of prices and generalized income. Therefore, telecommuting adoption is viewed as a trade-off among the prices of telecommuting itself, substitutes, and complements, as well as generalized income and situational constrains incurred by the employee. The underlying rationale is interpreted by elasticity analysis of aggregate telecommuting demand, based on an adoption model, with respect to various decision variable. The results indicate that the elasticity with respect to the price that the employee may incur in order to telecommute is the largest one, and the elasticity with respect to the living space at home is the second one. Additionally, all of the elasticities found in the group of employees currently commuting by private transportation are greater than the corresponding ones found in the group of transit riders. These findings are expected to have significant implications of transportation policies. This revised version was published online in June 2006 with corrections to the Cover Date.     

Car use,commuting and urban form in a rapidly growing city: evidence from Beijing

The links between urban form and travel behaviour have been widely studied in the field of travel demand management. However, the existing literature is dominated by case studies from the developed countries. A study of a city in a developing and industrialising country can add some fresh evidence to the debate on the impacts of urban form on travel patterns. Using household survey data from Beijing, this paper finds that aspects of urban form have significant effects on workers' car use and the duration of travel by car in journeys to work, while controlling for socio-economic factors and households’ preferences related to residential location. The sprawling patterns of land development play a negative role in reducing motorised commuting trips and shortening vehicle hours travelled in the current processes of rapid urban expansion and motorisation. Since urban sprawl is greatly influenced by growing market forces, the findings in this paper reveal the negative effects of regulation–liberation of land development management on travel behaviour modification.     

Travel demand model system for the information era

The emergence of new information technologies and recent advances in existing technologies have provided new dimensions for travel demand decisions. In this paper we propose a comprehensive travel demand modeling framework to identify and model the urban development decisions of firms and developers and the mobility, activity and travel decisions of individuals and households, and to develop a system of models that can be used by decision makers and planners to evaluate the effects of changes in the transportation system and development of information technologies (e.g. various tele-commuting, tele-services and Intelligent Transportation Systems).The implementation of an operational model system based on this framework is envisioned as an incremental process starting with the current best practice of disaggregate travel demand model systems. To this end, we present an activity-based model system as the first stage in the development of an operational model system.