REGULARITIES IN TRAVEL DEMAND: AN INTERNATIONAL PERSPECTIVE

By Andreas Schäfer. 2000

268 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/fee948eb499b0e9160195fb67b4ad0eb626f430c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. S. Gössling
2. P. Peeters
3. G. Dubois
4. G. D. de Jong
5. D. Metz
6. M. Pieters
7. B. Ó. Gallachóir
8. Kang-Rae Ma

In Renewable Energy, Sustainability and the Environment

1. S. Gössling
2. D. Metz
3. G. Dubois
4. B. Ó. Gallachóir
5. Kang-Rae Ma
6. A. Vo
7. David Bassett
8. U. Fahl

Citations in the corpus

• Energy and emissions forecast of China over a long-time horizon (2011, methodology): “The long term development of these transport indicators are drawn on various works done by Schäfer [60] and Rühle [61].”
• The Myth of Travel Time Saving (2008, background): “There is a good deal of data on average travel time from other sources which have been reviewed by Schafer and Victor (2000), Schafer (2000) and Mokhtarian and Chen (2004), building on the seminal earlier compilation of Zahavi and Talvitie (1980).”
• Excess Commuting: A Critical Review (2006, background): “…countries indicates that commuting distances have increased in the past several decades, but travel times have shown no clear pattern (for daily mobility for seven Organization for Economic Co-operation and Development (OECD) countries, see Schafer, 2000), implying that faster modes are being used.”
• Trends in income and price elasticities of transport demand (1850–2010) (2012, background): “Yet, historically and across cultures people’s travel distances have been bound by their monetary and time budgets (Schäfer, 2000).”
• Saturation of Demand for Daily Travel (2010, background): “Currently, each year some 20 000 individuals fill in seven-day travel diaries.1 There are methodological issues associated with such time series data (Schafer, 2000; Mokhtarian and Chen, 2004; Van Wee et al., 2006; Metz, 2008a).”
• The Built Environment and Motor Vehicle Ownership and Use: Evidence from Santiago de Chile (2010, background): “The latter two cases would result in increased total travel, consistent with the idea of constant travel time budgets (e.g., Schäfer, 2000).”
• The future tourism mobility of the world population: Emission growth versus climate policy (2011, background): “The link between speed and average distance resembles the idea of constant time budgets for travel (see Schafer, 2000; Schafer and Victor, 1999).”
• Global environmental consequences of tourism (2002, methodology): “This share might be somewhat different in reforming and developing countries, because even though the share of income spent for mobility and the time spent for daily travel may be similar (Schafer and Victor, 1999; Schafer, 2000), it can be assumed that the share of leisure-related purposes is lower”
• Transportation Costs and the Spatial Organization of Economic Activity (2014, unknown): “Schafer (2000) investigates these shares using older and somewhat more extensive national accounts data and finds that across countries the average expenditure share for household travel is about 11% with a standard deviation of about 3%.”
• Comparison of car ownership models (2004, background): “A disc u sion of international evidence on these assumptions can be found in Schafer (2000).”
• Walking, cycling, and obesity rates in Europe, North America, and Australia. (2008, methodology): “Germany, the Netherlands, Norway, Switzerland, and the United States are examples of countries that use this technique.(14) Other factors limiting comparability between surveys are the response rate, method of survey administration, and the inclusion/exclusion of weekend Page 5 of 35 Journal of Phys”
• Understanding urban human activity and mobility patterns using large-scale location-based data from online social media (2013, background): “These efforts, however, demonstrated that individual mobility patterns are strongly related with land-use patterns as well as the built environment of a city, and individual daily travel patterns exhibit great regularity [9, 10, 11, 12, 13].”