introduction
In industrial societies, and also in developing countries, automobile travel is increasingly associated with pollution, congestion and urban sprawl, entailing social and economic costs for both drivers as well as communities. Increasing travel volume and longer average commute, much of it spent stuck in traffic, are taxing community and private resources. Experts from various disciplines agree that it is desirable to manage this increase and at the same time slow the rate of growth. Building additional highways is not considered a desirable alternative in terms of both ecological and monetary costs.
Under these conditions, virtual mobility, involving the use of interactive technologies, may prove to be a viable alternative for activities that otherwise require physical transport. It can aid in the reduction of miles traveled and resulting environmental, social and economic impacts. Interactive applications include telework, telebanking, teleshopping, telemedicine and distance learning (DL), which generate considerable revenue from sources other than limited household media and communication budgets (Mundorf & Bryant, 2002).
While there is some empirical research on the impact of interactive technologies on travel behaviors, many of the potential benefits have yet to be realized. Research on the traffic impact of DL is even more limited. Besides technical factors and economic cost, the primary reason is human behavior. In industrial societies, we continue to engage in a pattern of single-occupant vehicle travel, in spite of increasing pollution, congestion and inconvenience.
IT and Transportation systems
Mobility has become an economic as well as a lifestyle attribute in advanced societies (Zelinsky, 1971). Zoche, Kimpeler and Joepgen (2002) point out that circular mobility (i.e., mobility without change in residence) has increasingly attracted research attention due to its environmental impact on pollution, congestion, noise and so forth. Since communication is no longer tied to physical transport, many functions that in the past required physical travel can now be fulfilled via communication media.
Mokhtarian (1990) conceptually discusses the variety of demand-and-supply relationships between telecommunications and transportation. All communications require some form of transportation and could take one or more of three forms: (i) transportation of people to meet face to face; (ii) transportation of objects, such as letters, books, newspapers and so forth; and/or (iii) transportation of electronic impulses. Mokhtarian uses historical, anecdotal, abstract and hypothetical examples to support the theory that “the actual amount of personal travel increases as part of a general expansion in communications, even though transportation’s share as a mode of communications declines” (p. 236). In other words, there is an overall steep increase in the amount of communication, but a more moderate increase in physical transport. Similarly,
Niles (1994) considers both the trip elimination effects of telecommuting and its trip generation potential. Notably, telecommunications may lead to greater urbanization and a wider range of economic activities, which can lead to increased traffic volume.
The positive impact of increased communication on physical transport of persons and goods has been reported in some studies. Canzler and Knie (2000), for example, found that the amount of time spent on travel has remained constant, but the distances covered tend to increase consistently. In a large-scale study, Zoche et al. (2002) analyzed the travel impact of virtual mobility in three areas: chat, online banking and online travel offerings. Even though all three modes have potential for travel reduction, only online banking led to a net reduction in miles traveled. For the other two areas, potential miles saved were offset by increased travel resulting from new acquaintances and group memberships (chat groups) or from travel bargains found online vs. traditional travel booking channels. The environmental impact of online shopping was less clear. While there is a substitution effect for trips to shopping centers and stores, deliveries to residential areas increase (Fichter, 2004).
Research on the traffic impact of DL is very limited. DL permits students to participate in many academic activities from home, from work or from satellite locations. It can replace library work, meetings and traditional face-to-face class meetings. The potential for reducing traffic to campus is considerable for a variety of student groups – particularly off-campus students, and even more so for working part-time and non-traditional students.
The issue of reducing or modifying travel through DL, particularly DL offered via Internet, has not been addressed in a satisfactory way. For instance, Shifter (2002) lists 29 motivating and 17 inhibiting factors for faculty participation in DL programs; the only one even remotely travel-related, is ranked 27 out of 29 motivators: “Ability to reach audiences that cannot reach classes on campus” (Shifter, 2002, Table 1). Similarly, Halsne and Gatta (2001) compared learner characteristics oftraditional and online students; again, none of them was related to transportation.
comparing virtual substitutes for mobility and travel
• Telework: Interactive communication technology has been shown to affect travel behavior, and a number of studies have explored the impact of communication and information technology (Niles, 1995). Much of this work is related to the impact of telework on travel behavior in a number of projects in California (Nelson & Niles, 1999).
While it is difficult to document the actual impact of telework, some encouraging data exist. Mokhtarian (1997) discusses the overall impact of telework on traffic volume. She reports a savings of 31 vehicle miles traveled per telecommuting occasion. The number of miles saved outweighed, by far, the amount of travel generated by telecommuters. Mokhtarian (1997) projects an overall savings potential of less than 1% of vehicle miles through reduced travel resulting from telework. The overall impact is limited due to the small number of teleworkers as a percentage of the total population. Furthermore, telecommuting tends to be primarily part-time, usually one or two days/week. For the typical telecommuter, 25% or 30% of work-related travel is eliminated, rather 80% or even 100%. In addition, the impact of telework on travel behaviors is limited due to effects of trip chaining and the reduced use of carpools and public transportation. Gartling, Gartling and Johansson (2000) assessed options for car-use reduction measures in Swedish households. Trip chaining and choice of closer venues was preferred for shopping and leisure activities; for work, alternatives such as biking and public transit were chosen. Subsequent travel diaries, however, revealed a lower level of reduction in car use than originally expected. Shopping and leisure trips, often not planned far in advance, are especially less likely to be subject to rationalization measures. However, the effect on traffic volume could become stronger with increased telework adoption; it is more pronounced in areas with higher concentrations of teleworkers.
Dholakia, Mundorf, Dholakia and Xiao (2004) explored factors facilitating adoption oftelework. Their findings indicate that work time flexibility, employer encouragement, educator as the occupation, having access to Internet at home, using computers longer than one hour a day, having more computers at home and perceiving that using Internet can reduce travel time to work and shopping are positively related to actual or intended use of the Internet as a substitute for travel to work.
• Distance Learning: Mokhtarian (1990) uses DL as one example to demonstrate the substitution impact of telecommunications on the demand for transportation via short-term direct, short-term indirect and long-term effects. Telecommunications, for instance, may make students better informed about on-campus events and activities and encourage them to travel to campus to attend such events (short-term direct). Time saved traveling to school for course-related purposes could be used for traveling to other places, such as friends’ homes, shopping centers, movie theaters, restaurants (short-term indirect). In addition, at the more aggregate level, universities that offer DL may reach new groups of students who have to travel, even if occasionally, since even perfect DL rarely eliminates all travel to campus (long-term effects). Another long-term effect might be that due to the reduced need for physical presence, more students decide to commute to campus from home rather than to live on or near campus. For student populations, traditional education has been delivered in face-to-face settings, requiring students to travel from home to classrooms. DL can eliminate many such trips. To address these issues, several studies were conducted at the University of Rhode Island. At the time of research, availability of DL courses was still limited; some Web-based courses were offered throughout the academic year, but many were offered during the summer to attract out-of-state students. Aside from specifically designed DL classes, use of the Internet during the academic year could reduce travel to campus in many ways; these include online registration, online library access, online contact with instructors, online submission of assignments, class Web sites and online course-related chat. Unlike an Online University, where all classes are based on DL, an institution such as the University of Rhode Island permits comparisons of DL’s travel impact with that of traditional in-class arrangements.
research findings
A primary focus of the research was to assess whether students use or intend to use the Internet to avoid traveling to campus. The first study found that 35% of the student sample has attempted to avoid travel via use of the Internet, while 58.6% have not and have no intentions to do so in the future. The following are key characteristics of those who intend to use the Internet as a substitute for travel (Mundorf, 2004). They:
• Tend to attend classes on fewer days (3.1 days/ week) compared to the those not using/not interested in using the Internet (3.9 days/week).
• Use computers at home more frequently (6.0 days/week), compared to the non-substitution group (4.75 days/week).
• Tend to perceive benefits of using the Internet to avoid traveling to campus in terms of saving money, adding flexibility and increasing choices.
• Are more likely to be part-time students (54%) than full-time students (36%).
• Are more likely than others to report using the Internet to obtain information (56% vs. 36%).
• Are more likely to be enrolled in DL courses (86% vs. 39%).
A second study, conducted in Fall 2001 (Dholakia & Kwon, 2003), focused on students enrolled in at least one course using DL (via the educational software package WebCT) to substitute for physical classroom time. At the end of the semester, the students were asked how many days per week they avoided coming to campus due to DL technology. Most (67%) responded 0 days. The remaining students responded they had avoided one to two days per week. Discriminant analysis determined the influence of four key variables relevant for DL-based travel avoidance (standardized coefficient):
• Number of days attending classes was negatively related (-.79).
• Overall attitudes toward Internet-based courses was the strongest positive predictor (.58).
• A greater ratio of DL courses was positively related (.47).
• Travel time to campus was positively related (.30).
Students with a course load that met on more days per week avoided fewer days of travel. To avoid more days of travel, students had to have favorable attitudes toward Internet-based courses, be enrolled in courses with greater use of WebCT and live farther away from campus.
To estimate the net effects of Internet use on travel time, R. Dholakia computed “nettime”—the (self-reported) net effect of Internet use on travel time (Dholakia et al., 2004). The results indicate that 29% of the respondents reported spending less time for travel because of Internet use, while 13% reported spending more time for travel. For most activities, students generally reported no change or did not respond. School- and work-related travel activities saw both increased and reduced time; shopping was associated with reduced time while socializing was associated with increased time.
• Comparing Telework and DL: Mundorf (2004) compared traffic impact of telework and DL along various dimensions (target group, payment, initiative, economic and behavioral goal and timeframe). He points out that the traffic impact of telework pertains to highways, is predictable, year round, mainly rush-hour and affects part- and full-time knowledge workers; while DL has more of a limited, seasonal effect in suburban areas at different times of the day mostly on part-time college and graduate students, as well as those in corporate training programs.
For many colleges in rural and suburban areas, travel to and from the campus can exacerbate traffic problems on roadways designed for light rural traffic. In urban areas, the impact of campus travel may be less, but students often have to commute to school, work and home through rush-hour traffic. This is a problem in particular for part-time students who work during the day and then travel to campus, often during peak hours.
To impact student travel behaviors, greater use of DL technology is warranted. Students who did not avoid any day of travel offered the following reasons: other courses (100%); library assignments (32%); other activities (26%); and work on campus (26%). When asked their future intentions, students who avoided travel also preferred the use ofWebCT and gave the avoidance of travel as one of the reasons for their preference. Almost 44% of students who preferred face-to-face instruction were able to avoid at least one day of travel to class.
There are limits, however, to DL’s impact on travel behaviors. Students are more likely to limit the number of days traveled to campus than totally eliminate travel—56% of the student sample indicated they would change the number of days traveled. Even those students who prefer DL courses were unable to avoid days of travel to campus (56%) because of other classes, work or library assignments on campus and group activities.
summary and conclusion
Most of the research discussed above addresses the potential rather than actual impact of Internet-based DL on travel behavior. The potential for using the Internet to substitute for traveling to campus exists. Our data—reflecting both student intentions and actual behaviors—suggest great potential for travel savings from the use of Internet-based technologies such as WebCT.
Our survey data also suggest that DL’s impact on travel behavior is limited by current deployment of DL technologies as well as student preferences. For US college students, at least, DL is more likely to impact the number of days traveled to campus. Group interactions, library assignments and on-campus work activities will continue to encourage travel to campus or other locations. Student preferences also favor face-to-face interactions that support travel: Perceived benefits of online learning are higher among those who report actually avoiding travel; similarly, students who have favorable attitudes towards Internet-based courses also report travel avoidance. Thus, there will be some degree of self-selection in the ways instructors and students decide to combine technology and face-to-face interactions in the teaching-learning process, which will pose limits to the impact of distance learning on travel behaviors. This self-selection is currently difficult to pinpoint, but it could be advantageous if universities learn to capitalize on this selectivity and develop appropriate market segmentation strategies.
Will the Internet totally replace travel ? Many college students prefer face-to-face interactions that involve travel to campus. Also, campus-based activities other than classes make travel to campus necessary in spite of DL availability. In fact, students will often conduct DL work while on campus. Individual differences are critical since those who prefer DL are more likely to actually reduce their travel to campus. And without a critical mass of DL courses, students may be able to delay travel to campus for one course, but not reduce the total number of trips. DL may be especially significant for returning students who have careers and families. The added convenience and safety might be a far greater factor for those students.
