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Recalling previous trips and the expenditures associated with them

PRESENT INTERNATIONAL COMPARABILITY ON DOMESTIC TOURISM BASIC DATA / QUESTIONNAIRE

Annex 9. Recalling previous trips and the expenditures associated with them

Recall Bias

“Memory effects” and “recall bias” are terms applied to the phenomenon of household survey respondents under-reporting long-distance travel activities when asked one month to one year after the event. Moreover, this under-reporting tends to vary directly with the elapsed time between the trip and the survey. Such bias has been documented in surveys of tourism spending (Mak, Moncur and Yonamine 1977; Bureau of the Census 1979, pp. 54, 59; Chau 1988, p. 3; Stynes and Mahoney 1989; Burd 1991, p. 13; Rylander, Probst and McMurtry 1995, p. 44; Lian and Denstadli 2003, p. 118), and led to the development in the U.S. of a “Cost Factor Model” to combine information that travelers could readily recall with costs per unit of travel activity derived from industry sources (Frechtling 1994, p. 374; Travel Industry Association of America 2002, pp. 113-115). First applied to 1972, the model is still employed today (as the Travel Economic Impact Model) to estimate domestic travel spending at the state level in the U.S. (Travel Industry Association of America 2004, p. 88).

The time elapsed between travel activity and its reporting in a household survey also affects recall of trips. A number of researchers have found the number of eligible trips reported declines with the length of the recall period (Meyberg and Brog 1981, p. 48; Rogers 1991, pp. 7-8; Statistics Canada 1992; Madre and Maffre 2001, p. 350; Lian and Denstadli 2003, p. 118). The American Travel Survey conducted the U.S. Government in 1995 asked respondents to recall trips taken in each of the three months prior to the interview. Analysis of the results indicated there were consistently more trips reported for a given month when the recall period was one month than when it was two or three months (Bureau of Transportation Statistics 1997, p. C-9). Armoogum and Madre (2003, p. 165) found in an investigation of the French National Personal Transportation Survey, “People appear to forget their business trips more often than their short private trips and the latter more than their long private trips.”

One means of reducing recall bias is to shorten the recall period as much as possible. Research on survey methods of measuring long-distance travel for the European Union (“Methods for European Surveys of Travel Behaviour, or “MEST”) found that recall periods “of up to eight weeks seem quality neutral but problems of memory recall can be observed for the earlier weeks of longer reporting periods.” (Axhausen et al. 2003, p. 302). However, Armoogum and Madre’s research on long- distance trip recall convince them to conclude, “most people remember . . . their long- distance trips for about one month” (2003, p. 154).

Of course, recall bias applies formally only to cases where the respondent had knowledge of an activity but memory lapse prevents him from acccurately reporting it. But this particular cause of non-response is not always the problem. Youssefzadeh (2003, p. 40) points out, “Although it would be interesting to know the allocation of costs between the employer and the traveler for business travel, experience with tourism surveys has shown that often respondents simply do not know the answer as the costs of their travel are not always transparent to them.” Other techniques, such as the Cost Factor Model, may fill in such gaps in tourism expenditure data collection.

The Diary Approach

Some survey managers have employed the “diary approach” to enhance trip recall accuracy. Respondents are contacted in advance of or during their trip and asked to record their travel activities (e.g., places visited, accommodations used, length of stay, expenditures) as they take place. Then the respondents either mail their diaries back to the manager or use the results as “memory joggers” to report activities in later interviews. Unfortunately, response rates in the 15-25 percent range raise serious concerns about respondent bias with this tool. (Woodside 1981, Hunt and Cadez 1981, Burke and Gitelson 1990). The MEST study found that virtually no household long-distance travel survey respondents used the travel diary provided them as a “memory jogger” (Axhausen, K.W., and Youssefzadeh, M. 2003, p. 103). The 1995 American Travel Survey employed diaries in pretesting their survey design in 1994. Survey managers found that only 41 percent of the respondents referred to their diaries to report trip activities in the subsequent interviews. (Bureau of Transportation Statistics 1997, p. D-4)

Armoogum and Madre suggest non-response be addressed by weighting procedures or imputation procedures (2003, p. 154). Weighting procedures attempt to correct for non-responses by increasing the weight given to respondent records. Weighting was used in the 1995 American Travel Survey to adjust for both household and trip non-response (Bureau of Transportation Statistics 1997, pp. C-4 – C- 6). Imputation procedures replace a unit or item non-response with the response given by respondents with similar characteristics. Several researchers have detailed how these might be carried out for long-distance travel and tourism surveys (Herry 2003, pp 77-79; Armoogum and Madre 2003, pp. 156-167; Han and Polak 2003, pp. 172- 186; Midenet and Fessant 2003, pp. 188-204; Lothaire and Toint 2003, pp. 244-253)

References

Armoogum, J., and J.-L. Madre (2003), “Weighting and correcting long-distance travel surveys”, in K. W. Axhausen, J.-L. Madre, J. W. Polak and Ph. L. Toint,

Capturing Long-Distance Travel, Baldock, Great Britain: Research Studies Press Ltd., pp. 151-169.

Axhausen, K. W., J.-L. Madre, J. W. Polak and Ph. L. Toint (2003), “Recommendations for a European survey of long-distance travel and associated research”, in Capturing Long-Distance Travel, Baldock, Great Britain: Research Studies Press Ltd., pp. 298-317.

Burd, Martha (1991), "The Economic Impact of Tourism Industries in B.C., draft," unpublished manuscript, British Columbia Ministry of Development, Trade and Tourism, Canada, September 27, 56 pp.

Bureau of the Census, U.S. (1979), 1977 Census of Transportation, National Travel Survey, Travel During 1977, Washington, D.C.: U.S. Government Printing Office, 406 pp.

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Chau, Peter (1988), "The Canadian Tourism Economic Impact System," paper prepared for Tourism Canada, Ottawa, Canada, August 1, 1988, 12 pp.

Frechtling, Douglas C. (1994), “Assessing the Impacts of Travel and Tourism– Measuring Economic Benefits”, in Travel, Tourism, and Hospitality Management: A Handbook for Managers and Researchers, 2nd edition, J. R. Brent Ritchie and Charles R. Goeldner, eds., New York: John Wiley & Sons, pp. 367-391.

Han, X. L., and J. W. Polak (2003), “Imputation with non-ignorable missing values: a stochastic approach”, in K. W. Axhausen, J.-L. Madre, J. W. Polak and Ph. L. Toint, Capturing Long-Distance Travel, Baldock, Great Britain: Research Studies Press Ltd., pp. 172-186.

Herry, M. (2003). “The 1995 Austrian NTS long-distance survey”, in K. W. Axhausen, J.-L. Madre, J. W. Polak and Ph. L. Toint, Capturing Long-Distance Travel, Baldock, Great Britain: Research Studies Press Ltd., pp. 72-107.

Lian, J.-I., and J.-M. Denstadli (2003), “How reliable are household surveys for the description of air travel?”, in K. W. Axhausen, J.-L. Madre, J. W. Polak and Ph. L. Toint, Capturing Long-Distance Travel, Baldock, Great Britain: Research Studies Press Ltd., pp. 110-119.

Lothaire, O., and Ph. L. Toint (2003), “A toolbox approach to data correction and imputation”, in K. W. Axhausen, J.-L. Madre, J. W. Polak and Ph. L. Toint,

Capturing Long-Distance Travel, Baldock, Great Britain: Research Studies Press Ltd., pp. 244-253.

Madre, Jean-Loup, and Joelle Maffre (2001), “Is It Necessary to Collect Data on Daily Mobility and Long-Distance Travel in the Same Survey”, Personal Travel: The Long and the Short of It, Conference Proceedings June 28-July 1, 1999, Washington, DC: Transportation Research Board, pp. 343-364.

Mak, James, James Moncur and David Yonamine (1977), "How or How Not to Measure Visitor Expenditure", Journal of Travel Research, XVI (Summer), pp. 1-4.

Meyberg, Arnim H. and Werner Brog (1981), "Validity Problems in Empirical Analyses of Non-Home-Activity Patterns", Transportation Research Record 807: Travel Demand Forecasting and Data Considerations, pp. 46-50.

Midenet, S.., and F. Fessant (2003), “New correction methods: Neural nets and self- organising maps”, in K. W. Axhausen, J.-L. Madre, J. W. Polak and Ph. L. Toint, Capturing Long-Distance Travel, Baldock, Great Britain: Research Studies Press Ltd., pp. 188-204.

Rogers, Judy (1991), A Review of Provincial Resident Travel Studies & the CTS: A Discussion Paper, Toronto, Canada: Ruston/Tomany & Associates, Ltd., August, 69 pp.

Rylander, Roy G., Dennis B. Propst and Terri R. McMurtry (1995), Journal of Travel Research, Vol. XXXIII, No 4 (spring), pp. 39-45.

Statistics Canada (1992), "Canadian Travel Survey, Changes Between 1992 and 190," May, 12 pp.

Stynes, Daniel J., and E. Mahoney (1989), "Measurement and Analysis of Recreational Travel Spending," Abstracts 1989 Symposium on Leisure Research, Alexandria, Virginia: National Recreation and Park Association, pp. Travel Industry Association of America (2002), Expenditure Patterns of Travelers in

the U.S., 2002 Edition, Washington, DC, 115 pp.

Travel Industry Association of America (2004), Impact of Travel on State Economies, 2004 Edition, Washington, DC, 101 pp.

Youssefzadeh, M. (2003), “Long-distance diaries today; Review and critique”, in K. W. Axhausen, J.-L. Madre, J. W. Polak and Ph. L. Toint, Capturing Long- Distance Travel, Baldock, Great Britain: Research Studies Press Ltd., pp. 28- 43.

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