Induced demand: Difference between revisions
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And Mokhtarian et al. (2002) paired eighteen California state highway segments whose capacities had been improved in the early 1970s with control segments that matched the improved segments with regard to facility type, region, approximate size, and initial volumes & congestion levels. Taking annual data for average daily traffic (ADT) and design-hour-traffic-to-capacity (DTC) ratios during the 21 years 1976-1996, they found the growth rates between the two types of segments to be “statistically and practically indistinguishable, suggesting that the capacity expansions, in and of themselves, had a negligible effect on traffic growth”.<ref>{{Cite journal|last=Mokhtarian, Samaniego, Shumway, & Willits|year=2002|title=Revisiting the notion of induced traffic through a matched-pairs study|url=https://www.researchgate.net/publication/263187449|journal=Transportation|volume=29|issue=2|pages=193–220|doi=10.1023/A:1014221024304|s2cid=152745459|via=}}</ref> |
And Mokhtarian et al. (2002) paired eighteen California state highway segments whose capacities had been improved in the early 1970s with control segments that matched the improved segments with regard to facility type, region, approximate size, and initial volumes & congestion levels. Taking annual data for average daily traffic (ADT) and design-hour-traffic-to-capacity (DTC) ratios during the 21 years 1976-1996, they found the growth rates between the two types of segments to be “statistically and practically indistinguishable, suggesting that the capacity expansions, in and of themselves, had a negligible effect on traffic growth”.<ref>{{Cite journal|last=Mokhtarian, Samaniego, Shumway, & Willits|year=2002|title=Revisiting the notion of induced traffic through a matched-pairs study|url=https://www.researchgate.net/publication/263187449|journal=Transportation|volume=29|issue=2|pages=193–220|doi=10.1023/A:1014221024304|s2cid=152745459|via=}}</ref> |
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==Induced demand in other areas== |
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'''Film Induced Demand''' |
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Film-induced demand (also referred to as film-induced tourism) is a relatively recent form of [[cultural tourism]] in which destinations that are included in media outlets such as television and films receive an increase in tourist visits. This is supported by several regression analyses that suggest a high correlation between destinations taking a proactive approach in order to encourage producers/studios to film at their location, and the tourism success in the area after the release of the movie.<ref>{{cite journal |last1=Hudgson & Richie |title=Film tourism and destination marketing: The case of Captain Corelli’s Mandolin |journal=Journal of Travel Research |date=1 May 2006 |doi=10.1177/0047287506286720}}</ref> This is consistent with induced demand theory. When the supply increases, in the form of media exposure to areas that were not regarded as tourist hotspots, the number of visitors increases, even though the majority of these new visitors would not have necessarily visited these areas previously. This is exemplified by a Travelsat Competitive Index study that indicated that in 2017 alone, approximately 80 million tourists made the decision to travel to a destination based primarily on its featuring in a television series or film. This figure has doubled since 2015.<ref>{{cite journal |last1=Velasco-Ferreiro, Parra-Meroño, Osácar-Marzal and Beltrán-Bueno |title=Academy of Strategic Management Journal |journal=Academy of Strategic Management Journal |date=2021 |volume=20 |issue=2S |url=https://www.abacademies.org/articles/analysis-of-the-impact-of-film-tourism-on-tourist-destinations-11323.html}}</ref> |
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One of the most prominent examples of film-induced demand is [[London King's Cross railway station]], which was made famous for featuring a fictional section known as platform 9 3/4 in the Harry Potter movie series, first appearing in ''[[Harry Potter and the Philosopher's Stone]]''. This fictional location was made into a real attraction in order to entice tourists to visit the train station, and a Harry Potter souvenir shop was constructed to capitalise on the increased interest in the series and the station. |
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== See also == |
== See also == |
Revision as of 19:20, 6 June 2022
Induced demand – related to latent demand and generated demand[1] – is the phenomenon whereby an increase in supply results in a decline in price and an increase in consumption. In other words, as a good/service becomes more readily available and mass produced, the price of a good/service goes down and consumers are more likely to buy it, meaning demand subsequently increases.[2] This is consistent with the economic theory of supply and demand.
In transportation planning, induced demand, also called "induced traffic" or consumption of road capacity, has become important in the debate over the expansion of transportation systems, and is often used as an argument against increasing roadway traffic capacity as a cure for congestion. Induced traffic may be a contributing factor to urban sprawl. City planner Jeff Speck has called induced demand "the great intellectual black hole in city planning, the one professional certainty that every thoughtful person seems to acknowledge, yet almost no one is willing to act upon."[3]
The inverse effect, or reduced demand, is also observed (see § Reduced demand).
Effect in transportation systems
Definitions
According to CityLab:
Induced demand is a catch-all term used for a variety of interconnected effects that cause new roads to quickly fill to capacity. In rapidly growing areas where roads were not designed for the current population, there may be significant latent demand for new road capacity, which causes a flood of new drivers to immediately take to the freeway once the new lanes are open, quickly congesting them again.
But these individuals were presumably already living nearby; how did they get around before the expansion? They may have taken alternative modes of transport, travelled at off-peak hours, or not made those trips at all. That’s why latent demand can be difficult to disentangle from generated demand—the new traffic that is a direct result of the new capacity. (Some researchers try to isolate generated demand as the sole effect of induced demand.)[1]
The technical distinction between the two terms, which are often used interchangeably, is that latent demand is travel that cannot be realised because of constraints. It is thus "pent-up". Induced demand is demand that has been realised, or "generated", by improvements made to transportation infrastructure. Thus, induced demand generates the traffic that had been "pent-up" as latent demand.[4][5][6][7]
History
Latent demand has been recognised by road traffic professionals for many decades, and was initially referred to as "traffic generation". In the simplest terms, latent demand is demand that exists, but, for any number of reasons, most having to do with human psychology, is suppressed by the inability of the system to handle it. Once additional capacity is added to the network, the demand that had been latent materialises as actual usage.[8]
The effect was recognised as early as 1930, when an executive of a St. Louis, Missouri electric railway company told the Transportation Survey Commission that widening streets simply produces more traffic, and heavier congestion.[9] In New York, it was clearly seen in the highway-building program of Robert Moses, the "master builder" of the New York City area. As described by Moses' biographer, Robert Caro, in The Power Broker:
During the last two or three years before [the entrance of the United States into World War II], a few planners had...begun to understand that, without a balanced system [of transportation], roads would not only not alleviate transportation congestion but would aggravate it. Watching Moses open the Triborough Bridge to ease congestion on the Queensborough Bridge, open the Bronx-Whitestone Bridge to ease congestion on the Triborough Bridge and then watching traffic counts on all three bridges mount until all three were as congested as one had been before, planners could hardly avoid the conclusion that "traffic generation" was no longer a theory but a proven fact: the more highways were built to alleviate congestion, the more automobiles would pour into them and congest them and thus force the building of more highways – which would generate more traffic and become congested in their turn in an ever-widening spiral that contained far-reaching implications for the future of New York and of all urban areas.[10]
The same effect had been seen earlier with the new parkways that Moses had built on Long Island in the 1930s and 40s, where
...every time a new parkway was built, it quickly became jammed with traffic, but the load on the old parkways was not significantly relieved.[11]
Similarly, the building of the Brooklyn-Battery Tunnel failed to ease congestion on the Queens-Midtown Tunnel and the three East River bridges, as Moses had expected it to.[12] By 1942, Moses could no longer ignore the reality that his roads were not alleviating congestion in the way he expected them to, but his answer to the problem was not to invest in mass transit, it was to build even more roads, in a vast program which would expand or create 200 miles (300 kilometers) of roads, including additional bridges, such as the Throgs Neck Bridge and the Verrazano Narrows Bridge.[13][14] J. J. Leeming, a British road-traffic engineer and county surveyor between 1924 and 1964, described the phenomenon in his 1969 book, Road Accidents: Prevent or Punish?:
Motorways and bypasses generate traffic, that is, produce extra traffic, partly by inducing people to travel who would not otherwise have done so by making the new route more convenient than the old, partly by people who go out of their direct route to enjoy the greater convenience of the new road, and partly by people who use the towns bypassed because they are more convenient for shopping and visits when through traffic has been removed.[15]
Leeming went on to give an example of the observed effect following the opening of the Doncaster Bypass section of the A1(M) in 1961. By 1998, Donald Chen quoted the British Transport Minister as saying "The fact of the matter is that we cannot tackle our traffic problem by building more roads."[16] In Southern California, a study by the Southern California Association of Governments in 1989 concluded that steps taken to alleviate traffic congestion, such as adding lanes or turning freeways into double-decked roads, would have nothing but a cosmetic effect on the problem.[14] Also, the University of California at Berkeley published a study of traffic in 30 California counties between 1973 and 1990 which showed that every 10 percent increase in roadway capacity, traffic increased by 9 percent within four years time.[16] A 2004 meta-analysis, which took in dozens of previously published studies, confirmed this. It found that:
...on average, a 10 percent increase in lane miles induces an immediate 4 percent increase in vehicle miles travelled, which climbs to 10 percent – the entire new capacity – in a few years.[17]
An aphorism among some traffic engineers is "Trying to cure traffic congestion by adding more capacity is like trying to cure obesity by loosening your belt."[18]
According to city planner Jeff Speck, the "seminal" text on induced demand is the 1993 book The Elephant in the Bedroom: Automobile Dependence and Denial, written by Stanley I. Hart and Alvin L. Spivak.[3]
Price of road travel
A journey on a road can be considered as having an associated cost or price (the generalised cost, g) which includes the out-of-pocket cost (e.g. fuel costs and tolls)[19] and the opportunity cost of the time spent travelling, which is usually calculated as the product of travel time and the value of travellers' time. These cost determinants change often, and all have variable effects on demand for transport, which tends to be dependent on the reason(s) as well as method of travel.[19]
When road capacity is increased, initially there is more road space per vehicle travelling than there was before, so congestion is reduced, and therefore the time spent travelling is reduced – reducing the generalised cost of every journey (by affecting the second "cost" mentioned in the previous paragraph). In fact, this is one of the key justifications for construction of new road capacity (the reduction in journey times).
A change in the cost (or price) of travel results in a change in the quantity consumed. Factors such as petrol prices, as well as fuel costs, are the most common variables that influence the quantity demanded for transport.[19] This can be explained using the simple supply and demand theory, illustrated in this figure.
Elasticity of transport demand
The economic concept of elasticity measures the change in quantity demanded relative to a change in another variable, most commonly price.[20] For roads or highways, the supply relates to capacity and the quantity consumed refers to vehicle miles traveled. The size of the increase in quantity consumed depends on the elasticity of demand.
The elasticity of demand for transport differs significantly depending on the reason people are choosing to travel initially. The clearest example of inelastic demand in this area is commuting, as studies indicate that most people are going to commute to work, regardless of fluctuations in variables such as petrol prices, as it is a required activity to generate income.[19] This exemplifies the fact that activities that yield a high economic benefit, in this case, financial gain in the form of income, tend to be inelastic. Whereas, travelling for recreational or social reasons have a high tolerance for price increases, and as such the demand for recreational travel when prices spike sees a sharp decline.[19]
A review of transport research suggests that the elasticity of traffic demand with respect to travel time is around −0.5 in the short term and −1.0 in the long term.[21] This indicates that a 1.0% saving in travel time will generate an additional 0.5% increase in traffic within the first year. In the longer term, a 1.0% saving in travel time will result in a 1.0% increase in traffic volume.
Sources of induced traffic
In the short term, increased travel on new road space can come from one of two sources: diverted travel and induced traffic. Diverted travel occurs when people divert their trip from another road (change in route) or reschedule their travel to avoid peak period congestion – but if road capacity is expanded, peak congestion is lower and they can travel at the time they prefer.
Induced traffic occurs when new automobile trips are generated. This can occur when people choose to travel by car instead of public transport, or decide to travel when they otherwise would not have.[22]
Shortening travel times can also encourage longer trips as reduced travel costs encourage people to choose farther destinations. Although this may not increase the number of trips, it increases vehicle miles travelled. In the long term, this effect alters land use patterns as people choose homes and workplace locations farther away than they would have without the expanded road capacity. These development patterns encourage automobile dependency which contributes to the high long-term demand elasticities of road expansion.[22]
Induced traffic and transport planning
Although planners take into account future traffic growth when planning new roads (this often being an apparently reasonable justification for new roads in itself – that traffic growth will mean more road capacity is required), this traffic growth is calculated from increases in car ownership and economic activity, and does not take into account traffic induced by the presence of the new road; that is, it is assumed that traffic will grow, regardless of whether a road is built or not.[22]
In the UK, the idea of induced traffic was used as grounds for protests against government policy of road construction in the 1970s, 1980s and early 1990s, until it became accepted as a given by the government as a result of their own Standing Advisory Committee on Trunk Road Assessment (SACTRA) study of 1994. However, despite the concept of induced traffic now being accepted, it is not always taken into consideration in planning.
Studies
A 1998 meta-analysis by the Surface Transportation Policy Project, which used data from the institute, stated that "Metro areas which invested heavily in road capacity expansion fared no better in easing congestion than metro areas that did not."[23]
On the other hand, a comparison of congestion data from 1982 to 2011 by the Texas A&M Transportation Institute suggested that additional roadways reduced the rate of congestion increase. When increases in road capacity were matched to the increase demand, growth in congestion was found to be lower.[24]
A study by Robert Cervero, a professor of City and Regional Planning at the University of California, Berkeley, found that "over a six-to eight-year period following freeway expansion, around twenty percent of added capacity is 'preserved,' and around eighty percent gets absorbed or depleted. Half of this absorption is due to external factors, like growing population and income. The other half is due to induced-demand effects, mostly higher speeds but also increased building activities. These represent California experiences from 1980 to 1994. Whether they hold true elsewhere is of course unknown."[25]
And Mokhtarian et al. (2002) paired eighteen California state highway segments whose capacities had been improved in the early 1970s with control segments that matched the improved segments with regard to facility type, region, approximate size, and initial volumes & congestion levels. Taking annual data for average daily traffic (ADT) and design-hour-traffic-to-capacity (DTC) ratios during the 21 years 1976-1996, they found the growth rates between the two types of segments to be “statistically and practically indistinguishable, suggesting that the capacity expansions, in and of themselves, had a negligible effect on traffic growth”.[26]
See also
References
Notes
- ^ a b Schneider, Benjamin (September 6, 2018) "CityLab University: Induced Demand" CityLab
- ^ Mann, Adam (17 June 2014). "What's Up With That: Building Bigger Roads Actually Makes Traffic Worse". Wired.
- ^ a b Speck 2012, p. 80
- ^ Mokhtarian, Patricia L. (ndg) "Understanding the Concept of Latent Demand in Traffic" State of California Department of Transportation
- ^ Clifton, Kelly and Moura, Felipe (January 2017) "Conceptual Framework for Understanding Latent Demand: Accounting for Unrealized Activities and Travel" abstract) Transportation Research Record Journal of the Transportation Research Board
- ^ Rodrigue, Jean-Paul (2016) "Transportation as a Derived Demand" The Geography of Transport Systems
- ^ Cervero, Robert (March 2001) "Induced Demand: An Urban and Metroplitan Perspective" United States Environmental Protection Agency; Federal Highway Administration, United States Department of Transportation; Eno Transportation Foundation
- ^ Vanderbilt, Tom (2008) Traffic: Why We Drive the Way We Do (and What It Says About Us) New York; Knopf. pp.154-156. ISBN 978-0-307-26478-7
- ^ Report of the Transportation Survey Commission of the City of St. Louis (1930), p.109, cited in Fogelson, Robert M. (2001) Downtown: Its Rise and Fall, 1880-1950 New Haven, Connecticut: Yale University Press. p.66. ISBN 0-300-09062-5
- ^ Caro 1974, p. 897
- ^ Caro 1974, p. 515
- ^ Caro 1974, p. 911
- ^ Caro 1974, pp. 96–97
- ^ a b Duany, Plater-Zyberk & Speck 2000, p. 88
- ^ Leeming, J. J. (1969). Road Accidents: Prevent or Punish?. Cassell. ISBN 0304932132.
- ^ a b Chen, Donald D. T. (March 1998) "If You Build It, They Will Come ... Why We Can't Build Ourselves Out of Congestion" Surface Transportation Policy Project Progress; quoted in Duany, Plater-Zyberk & Speck 2000, p. 89
- ^ Salzman, Randy (December 19, 2010) "Build More Highways, Get More Traffic" The Daily Progress, quoted in Speck 2012, p. 82
- ^ Duany, Plater-Zyberk & Speck 2000, p. 89
- ^ a b c d e Rodrigue, Jean-Paul (2020). The Geography of Transport Systems. New York: Routledge.
- ^ Hayes, Adam (August 1, 2021). "Elasticity". Investopedia.
- ^ Goodwin, P. B. (1996). "Empirical evidence on induced traffic: A review and synthesis". Transportation. 23: 35–54. doi:10.1007/BF00166218. S2CID 154827067.
- ^ a b c Litman, T. L. (2011). "Generated Traffic and Induced Travel: Implications for Transport Planning" (PDF).
- ^ Speck 2012, p. 83
- ^ Texas A&M Transportation Institute. "2012 Urban Mobility Report". Retrieved May 14, 2013.
- ^ Cervero, Robert (Spring 2003). "Are Induced-Travel Studies Inducing Bad Investments?" (PDF). University of California Transportation Center. Archived from the original (PDF) on 2019-01-30. Retrieved April 5, 2017.
- ^ Mokhtarian, Samaniego, Shumway, & Willits (2002). "Revisiting the notion of induced traffic through a matched-pairs study". Transportation. 29 (2): 193–220. doi:10.1023/A:1014221024304. S2CID 152745459.
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: CS1 maint: multiple names: authors list (link)
Bibliography
- Caro, Robert (1974). The Power Broker: Robert Moses and the Fall of New York. New York: Knopf. ISBN 978-0-394-48076-3. OCLC 834874.
- Duany, Andres; Plater-Zyberk, Elizabeth; Speck, Jeff (2000). Suburban Nation: The Rise of Sprawl and the Decline of the American Dream. New York: North Point Press. ISBN 0-86547-606-3.
- Speck, Jeff (2012). Walkable City: How Downtown Can Save America, One Step at a Time. New York: North Point Press. ISBN 978-0-86547-772-8.
Further reading
- Hart, Stanley I. and Spivak, Alvin L (1993). The Elephant in the Bedroom: Automobile Dependence and Denial; Impacts on the Economy and Environment. Pasadena, California: New Paradigm Books. ISBN 0932727646.
External links
- Giles Duranton, Matthew A. Turner (2010), The Fundamental Law of Road Congestion: Evidence from US cities, University of Toronto
- UK Department for Transport guidance on modelling induced demand
- A statistical analysis of induced travel effects in the US mid-Atlantic region (Fulton et al.), Journal of Transportation and Statistics, April 2004 (PDF)
- Todd Litman (2001), “Generated Traffic; Implications for Transport Planning,” ITE Journal, Vol. 71, No. 4, Institute of Transportation Engineers (www.ite.org), April, 2001, pp. 38–47.