As Lovejoy (2003) argues, âThe best way to measure the impact of visitor ..... when use of a resource is promoted, an inventory and sustainable audit is recom-.
Collecting and Using Visitor Spending Data JAMES J. WILTON AND NORMA POLOVITZ NICKERSON
Visitor spending is a necessary component of economicimpact analysis, but detailed expenditure categories rarely are reported and used as tools for marketing and policy decisions. This article shows that spending by visitors attracted to Montana’s natural resources accounted for 76% of traveler spending in the state. Average daily spending by visitors primarily attracted to fishing was the highest pergroup per-trip expenditure ($1,641.26) and the longest length of stay (9.3 nights), with fishing outfitters and guides receiving the largest share of these visitors’ dollars. Visitors attracted to Glacier National Park had the highest total contribution of dollars to the state. Implications of the study suggest that conservation of Montana’s natural resources is paramount to a thriving tourism industry. Policies and regulations related to waterways, mountain view sheds, and open space need to reflect the important economic contribution of what attracts visitors to the state. Keywords: attractions; expenditure-based segmentation; market segmentation; Montana; natural resources; policy; spending The economic impact of tourism is a fundamental selling point for pursuing the development of tourism, and consequently, it has been studied and analyzed substantially over the years. For example, the economic impact of special events (Chhabra, Sills, and Cubbage 2003; Crompton, Lee and Shuster 2001; Dwyer, Forsyth, and Spurr 2005; Jackson et al. 2005; Tyrrell and Johnston 2001), specific sites or towns (Frechtling and Horvath 1999; Johnson and Sullivan 1993), recreation activities (Upneja et al. 2001), geographic regions (Chhabra 2004; Smith 2005; Taylor, Fletcher, and Clabaugh 1993), and states and countries (Lovejoy 2003; Perez and Sampol 2000; Wang, Tian, and Cook 2004; Wilton 2004) has been reported and used extensively for tourismpolicy development. Each of these studies, however, necessarily uses primary or secondary expenditure data as a core component of the economic-impact analysis. Yet, the discussion related to the collection and uses of expenditure data has not been as prevalent in the literature as economic impacts. As shown by Vaughan, Farr, and Slee (2000), the data required for an economic-impact study consist of information about the operational characteristics of businesses, the spending of visitors, and the spending of residents of the area. Because it brings in money from outside the area, visitor spending is the main focus of tourism economic-impact analyses. More than two decades later, the sentiment by Ritchie (1984) holds true that while measures related to economic-impact
assessment are conceptually simple, the actual collection of such information is extremely difficult. Emphasizing the importance of visitor expenditures to any tourism economics discussion, James Mak (2004) concludes, “Big gaps remain in our understanding of tourist spending behavior. Having quality information on tourist expenditures also helps us to better understand the economic benefits of tourism to host communities. Hence . . . we need better tourism expenditure information” (pp. 62–63). This article looks at the key initial stage of tourismimpact analysis—that of actual visitor expenditures. First, the methodology for collecting expenditure data will be presented, followed by a discussion on ways to segment the data. Next, we will look at the implications of these segmented data for policy and marketing decisions. Taken together, these discussion points hopefully will give attention to the importance of acquiring quality spending data.
VISITOR SPENDING Accurately assessing the economic impact of tourism is difficult because there is no simple measure of how much travelers spend. As Lovejoy (2003) argues, “The best way to measure the impact of visitor spending is to use surveys to determine the amount and type of goods that travelers tend to purchase, and then to estimate the portion of output visitors support in key industries” (p. 7). To obtain visitor-spending data, surveying actual visitors is the most straightforward method. Many times, however, visitor spending is obtained through the use of tourism satellite accounts (TSAs) or other accounting models that can produce an estimate of spending indirectly (Okubo and Planting In memory of my friend and colleague, Jim Wilton. James (Jim) passed away on March 26, 2006, of natural causes, leaving behind his wife, Heidi, and baby girl, Amanda. He was the assistant director and economist for the Institute for Tourism and Recreation Research at the University of Montana. Jim is remembered for his love of the outdoors, his honesty, his integrity, and for living each day to its fullest. He brought professionalism and laughter to our office. I will miss him terribly. Norma Nickerson, PhD, is director of the Institute for Tourism and Recreation Research, College of Forestry and Conservation at the University of Montana. Funding for this study came from the Montana statewide Lodging Facility Use Tax. Journal of Travel Research, Vol. 45, August 2006, 17-25 DOI: 10.1177/0047287506288875 © 2006 Sage Publications
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AUGUST 2006
1998) but not always through direct surveying of visitors. Visitor spending—as reported by the visitors themselves— can provide an accurate basis for subsequent economicimpact analysis as well as comparisons to other industries. However, visitor spending often is reported in lump sums (i.e., total-group or per-day expenditures for various visitor groups). For example, Walker and Joppe (2004) used demographics, specifically gay marriage, to report probable spending by gay couples. Numerous researchers have studied total spending based on activity such as gambling (Noh, Huh, and Holecek 2004), attending a special event (Martin et al. 2003), and even shrimp consumption by visitors (McElroy et al. 2005). Package-tour travelers spend almost double on lodging than other travelers (Tasci, Aziz, and Holecek 2003), whereas total spending based on Internet users or nonusers also has been reported (Andereck, Ng, and Knopf 2003; Kim and Morrison 2003). Detailed expenditure patterns were presented by Chhabra (2003) for visitors to Sacramento County, California, showing that more expenditures were on lodging, followed by shopping, food and beverage, and finally, gasoline. These detailed expenditures are not as prevalent in the literature as total daily expenditures, which eliminates the ability to segment visitors by expenditures. Detailed visitor spending, as specified by the visitor, nonetheless has its own challenges. Recently, Stynes (1998) elaborated on the specific technical aspects of measuring visitor spending. Considerations for collecting valid data include reliable visitation data, an accurately defined study region, clearly defined spending categories, a definitive unit of analysis (e.g., visitor party per day), and a separation of residents from nonresidents. Unrepresentative samples found by Sun (2005) in a study of three national parks showed that the visitor-survey projects of the National Park Service overestimated spending because of sampling locations and seasonality. In addition, to reduce the possibility of error in visitor spending, surveys need to be designed with precise questioning, and surveying needs to occur close to the time of the spending behavior to reduce recall bias (inaccurate recollection of spending) and telescoping (reporting expenditures beyond the study area; Stynes 1998). Recall bias often occurs when spending is documented after the travel period (days or months later) and is seen by Stynes as the most likely error to occur. Most research on recall bias has indicated that errors usually are caused by spending underestimation (Frechtling 1994; Howard, Lankford, and Havitz 1991; Stynes and Mahoney 1989). These studies show that the longer the length of elapsed time between the visit and when respondents were asked to recall trip expenditures, the more likely respondents underestimated their actual expenditures. Zhou (2000), however, found in a conversion study in Frankenmuth, Michigan, that visitors inflated their reported expenditures if enough time elapsed between spending and recall. Zhou does inquire as to how much time is needed to trigger the memory overestimation. In another study, Breen, Bull, and Walo (2001) found that recall bias occurred in exit interviews of participants to an Australian sporting event, but diary methods (both mailback and onsite) provided more accurate expenditure reporting. Interestingly, males who were interviewed with their group of peers while exiting the event tended to report higher levels of spending in some categories than did females.
A potential social bravado or peer pressure appeared to be occurring, the authors concluded. It is, therefore, apparent that recall bias has been observed in many studies (Breen, Bull, and Walo 2001; Faulkner and Raybould 1995; Frechtling 1994; Howard, Lankford, and Havitz 1991; Scott and Amenuvegbe 1990). Findings from these studies may raise concerns about the continued reliance by some researchers on collecting spending data after the visitor’s travels. Many United States states and larger communities use the services of private research companies for acquiring spending data. These companies generally use a major consumer mail panel that is weighted to be representative of the study area in terms of key demographic characteristics. However, when only 5 to 10% of the population originally agrees to be a part of the study panel, self-selection bias likely may result (Hwang and Fesenmaier 2002). In addition, these household surveys typically ask respondents to recall their expenditures on a trip taken a month or more earlier. If recall bias is a problem in exit interviews that are conducted as the visitor leaves an area, respondent recollection of expenditures from a month earlier may cause even greater recall bias, and hence, create greater error in the overall estimate of visitor spending. However, as Zhou (2000) points out, collecting expenditure data close to the time of spending can be costly, and therefore, impractical for many research entities. In survey research, when all potential forms of bias cannot be controlled or accurately measured, reasonable caution in interpreting the results should be taken and limitations appropriately voiced. The purpose of this article is to present a variety of ways to segment visitor-spending data so as to view the information from different lenses and to assist in policy development and marketing decisions. This article provides an expenditure-based segmentation of visitors to the state of Montana, U.S.A.
METHODOLOGY Year-long nonresident visitor studies have been conducted in Montana every 4 or 5 years since 1988 to assess visitor-spending patterns, among other things, in the state. For this analysis, nonresident travelers to Montana in 2001 were examined (Nickerson, Sutton, and Aronofsky 2002).
Study Population The population of travelers was defined as those persons who entered Montana by private vehicle or commercial air carrier during the study period and whose primary residence was not in Montana at the time (Nickerson, Sutton, and Aronofsky 2002). Specifically excluded from the study were those persons who entered Montana on a roadway while traveling in plainly marked commercial (e.g., scheduled or chartered bus or semi truck) or government vehicles. Also excluded were those travelers who entered Montana by train (because of comparatively minimal visitor use and lack of resident-to-nonresident proportions) and out-of-state college students temporarily living in Montana. Other than these exclusions, the study attempted to assess all types of travel to the state, including travel for pleasure, business, passing through, or other reasons.
JOURNAL OF TRAVEL RESEARCH
Population Estimation Model A population estimation model was designed to identify all members of the study population by entry location and month of entry into the state (Nickerson, Sutton, and Aronofsky 2002). Thirty-nine highway entry points and the state’s eight main airports that have regularly scheduled commercial flights were used in the population estimation model. These entry points represent more than 98% of all traffic into Montana. The model is based on monthly passenger counts obtained from the Montana Aeronautics Division and traffic counts from the Montana Department of Transportation, United States Customs, and the departments of transportation from adjacent states. The passenger and traffic counts are applied to the resident-to-nonresident proportions for each entry location used in the model. Traffic proportions were obtained through hour-long observations on random days and times (any time from 8:00 a.m. to 8:00 p.m.) at each entry point throughout the year. All traffic entering Montana during the sample period was recorded as a resident, nonresident, or unknown based on license plate. It was assumed that the unknowns (mostly because of unreadable license plates) were both resident and nonresident plates, and therefore, they were not included in the proportions. The number of observations per highway entry was determined according to relative traffic volume. In other words, the highway entry with the greatest traffic volume received the highest proportion of traffic observations, and so on. Likewise, throughout the year at airports, surveyors asked each outbound passenger boarding predetermined random flights whether he or she was a resident of Montana or not. Surveyors also were assigned to specific airlines and airports based on passenger volume to reflect the proportion of air travel by city and airline so as to avoid oversampling smaller flights. All departing flights had multiple sampling days throughout the year.
Survey Methodology Highway travel groups (all the people in one vehicle) were intercepted at travel-neutral areas within the state. These are areas where highway travelers are likely to stop while traveling in the state, regardless of their travel mode (i.e., car, motorcycle, RV). For the highway intercepts, travelneutral areas included gas stations in 30 communities, nine rest areas located throughout the state, and three Canadian border crossings. A variety of independent and national gas station chains were used to increase the chance of intercepting visitors who only use one brand of gas. To reduce selection bias based on length of stay (i.e., visitors staying longer would have a higher chance of selection), 24 of the 30 intercept communities were located within 80 miles of a border (please note that it is 700 miles across Montana by Interstate east-west and nearly 400 miles by Interstate north-south). This method, however, increases the chance of underestimating day trippers, because they may not stop for gas or stop at a rest area while in the state. Yet, it was determined that erring on the side of conservative estimates because of some of these travelers was reasonable, especially in terms of expenditures and economic-impact analysis. Air travelers were intercepted in the boarding area of the eight Montana airports as they waited for their outbound
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flight. An air-travel group consisted of those who traveled and paid together as a unit (e.g., family, couple, etc). If individuals were flying together but paying separately, they each could be interviewed as a separate visitor. Because visitors must leave the state by air or highway, practically all nonresident visitors had a chance to be intercepted at one of the numerous intercept locations. Data were collected from the travel groups once the groups were intercepted. No group or individual was surveyed more than once during the trip. If intercepted a second time, visitors typically indicated that they already had been intercepted, and the survey process was terminated. The intercept data included point of entry into the state, group size and type, primary residence, travel method, purpose of trip, anticipated length of stay in Montana, direction of travel, and planned exit. These front-end data were obtained from 94% of all intercepted travel groups. The majority of those refusing to answer front-end questions were day-trippers who were only in the state for a gasoline purchase and then returning to their residence over the state line. After the front-end answers were collected, the travel groups were asked to accept and complete a diary questionnaire of their visit to Montana and to return it by mail in a provided postage-paid envelope. During the study period, 11,467 groups were contacted, and questionnaires were handed to 10,737 groups. Useable questionnaires were returned by 4,220 groups for a response rate of 39%. Because of the nature of the study (surveying traveling groups) and the requisite prompt recording of expenditures to reduce recall bias, no follow-up measures (i.e., reminder postcards or replacement questionnaires) were used to increase response rate. To reflect the traveler population, survey data were weighted by point of entry and purpose of trip based on the front-end data numbers. After weighting these items, all other corresponding front-end variables were compared to survey data variables with no significant differences found. The diary-questionnaire format for this study was a twopage, front and back booklet-style survey instrument. Expenditure questions used in this survey are shown in Table 1. Travelers were asked to report their spending for one day of their trip. The day to report their expenditures was the current day, the next day, or two days from the intercept day, depending on how many more days the visitor would be in the state. Because visitors were intercepted during any day of their travels in the state, this random assignment of expenditure reporting assured representation of all possible days a visitor would be in Montana from their first day through the last day of their visit. All airport travelers departing on the selected airline were intercepted in the boarding area and alternately were assigned to report spending either on that day or the previous day. Respondent expenditures were reported in 11 spending categories in addition to the town in which the expenditure occurred. This location variable allowed for further geographic segmentation. Expenditure ranges in each spending category were analyzed, and outliers above two standard deviations were delimited to the highest value. While some researchers suggest completely eliminating the outliers, it was decided for the purpose and context of this study that these expenditures are valid responses and were therefore delimited. Rather than lose these legitimate purchases entirely, they were kept,
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AUGUST 2006 TABLE 1 NONRESIDENT VISITOR SURVEY EXPENDITURE QUESTIONS
Please record all of your travel group’s expenditures for the day of your trip indicated on the envelope accompanying this questionnaire. Enter the amount and the town where you spent money during your visit in Montana. If you spent money in more than one Montana town, use a separate line for each place you spent money. Use the “Additional” category if the expenditure type does not match those listed. Expenditure Type Campground facility, RV park Hotel, motel, bed & breakfast, etc. Gasoline, oil Restaurant, bar Groceries, snacks Retail goods__________________ Please specify Retail goods__________________ Please specify Retail goods__________________ Please specify Outdoor guides, outfitters Auto/RV rental, repair Transportation fares (e.g., taxi fare) Entrance fees, licenses, admissions Additional __________________ Please specify Additional __________________ Please specify
Amount Spent on Assigned Day
Montana Town
$___________________________ $___________________________ $___________________________ $___________________________ $___________________________ $___________________________ $___________________________ $___________________________ $___________________________
_________________ _________________ _________________ _________________ _________________ _________________ _________________ _________________ _________________
$___________________________
_________________
$___________________________
_________________
$___________________________ $___________________________ $___________________________ $___________________________ $___________________________ $___________________________ $___________________________
_________________ _________________ _________________ _________________ _________________ _________________ _________________
$___________________________
_________________
but at two standard deviations of the mean. When visitors reported package tours as a total expenditure item, calls were made to the tour providers (e.g., ski resort or dude ranch), and allocation of expenditures was made based on that information. For this study, variables for the expenditure-based segmentation included primary purpose of trip, main attraction to Montana, repeat or first-time visitors, and visitors with or without children younger than 18 on the trip. These variables were single-response categorical variables in which the respondent could choose only one answer out of the choice set. For example, the primary-attraction variable was used, in which each respondent was forced to choose the overall attraction rather than many attractions, thereby avoiding the possibility of a respondent’s being counted in more than one expenditure segment. Finally, spending patterns for nonresident visitors to Montana in 2001 were inflated to 2004 dollars to show more up-to-date spending amounts.
RESULTS AND DISCUSSION Tables 2 through 4 show the different expenditure categories, average daily expenditures, and average length of stay for each visitor segment. Visitors whose primary trip purpose was vacation had a higher average daily expenditure than all other purposes at $146.03, compared to the next highest expenditure of $128.10, which was the other purpose
category consisting of attending funerals, buying property, and other reasons (Table 2). While length of stay for the other purpose was slightly longer than vacationers (6.53 compared to 5.72 nights), vacationers consisted of 43% of all travelers, whereas the other group was only 6%. This initial analysis of traveler length of stay, percent of the traveler population, and daily expenditures suggests that vacationers by far are the highest value visitor to Montana (at least in an economic sense). In the survey, 62% of visitors indicated vacation as one reason for their trip. Members of this group then were asked what attracted them to Montana as well as their primary attraction. Because of how the question was structured, vacationers became the population for the subset of primary attraction to the state. Table 3 highlights the top nine attractions to Montana listed in the questionnaire. Six of the nine attractions, including the top four, are natural-resource based. Yellowstone and Glacier National Parks were the top two attractions in terms of total respondents, but were third and fourth, respectively, in terms of average daily expenditures. Fishing visitors had the highest daily expenditure of $176.29, followed by open space at $146.49. Comparing total direct expenditures (length of stay × average daily expenditures × sample size), visitors whose primary attraction was Glacier National Park had the highest direct expenditures ($384,000) in the state, followed by those visitors whose main attraction was friends and relatives ($291,000). The next highest expenditure group was visitors mainly attracted to Yellowstone National Park ($247,000), followed by those attracted to
JOURNAL OF TRAVEL RESEARCH
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TABLE 2 AVERAGE DAILY EXPENDITURES BY PURPOSE OF TRIP AND MODE OF TRANSPORTATION Primary Purpose of Trip
Sample size Percent of population** Gasoline, oil Retail sales Restaurant, bar Hotel, motel, B&B, etc. Groceries Auto rental, repairs Outfitter, guide Licenses, entrance fees Campground, RV park Transportation fares Miscellaneous expenses, services Total average daily per group Average length of stay*** Average trip expenditures Total Direct Expenditures of Sample
Vacation
VFR*
Pass-Through
Business
Other
1,784 43% $27.05 $31.23 $28.85 $22.16 $12.38 $4.86 $7.59 $5.45 $4.11 $0.14 $2.22 $146.03 5.72 $835.29 $1.5 mil.
647 16% $25.46 $31.04 $23.21 $11.49 $9.37 $4.03 $1.47 $1.78 $1.00 $0.08 $1.18 $110.11 5.43 $597.90 $387,000
1,100 26% $32.09 $7.75 $16.46 $15.32 $4.29 $3.34 $0.56 $1.10 $1.53 $0.17 $1.28 $83.87 1.35 $113.22 $125,000
378 9% $24.16 $18.46 $30.85 $28.81 $5.94 $9.53 $1.88 $0.81 $0.26 $0.92 $1.76 $123.38 4.57 $563.85 $213,000
191 6% $34.66 $24.07 $26.89 $22.17 $9.19 $6.40 $0.00 $1.40 $0.90 $0.00 $2.41 $128.10 6.53 $836.49 $160,000
*Visiting friends and relatives. **Valid percent recorded after removing 386 missing values. Shopping (2%) attraction was not included. ***Delimited to 30 nights.
open space ($264,000). (Note: The expenditures shown here represent the sample but become much larger in scale when applied to the nonresident population estimates. For example, when the 4% of respondents whose primary attraction to Montana was fishing is applied to the total estimated $1.96 billion in nonresident direct expenditures, total nonresident fishing becomes an estimated $7.8 million direct nonresident contribution to the state.) There are a number of ways to use these data in relationship to policy and marketing. First, average daily expenditures provide insight about the high-value visitor. The top four expenditure groups were visitors primarily attracted to fishing, open space, Yellowstone National Park, and Glacier National Park. From a policy perspective, these main attractions are all natural-resource-based attractions that bring tourism dollars into the state. With nonresident tourism as one of the top economic sectors of the state (Polzin 2005; Wilton 2004), policy makers need to be aware of consequences of laws and regulations that could reduce visitors who are attracted to these Montana resources. Visitors who are attracted to Montana primarily for fishing spend the longest length of time in the state and the most dollars per day of all groups (Table 3). This suggests that the state needs to preserve streams, rivers, and lakes to ensure a continued sport-fishing industry. From an ecological viewpoint, this requires standards related to use of adjacent lands so as to encourage conditions favorable to fish habitat. Some of this already has taken place with the example of the Blackfoot Challenge (Bureau of Land Management 1997), in which a diverse group of concerned citizens (ranchers, homeowners, state parks, Bureau of Land Management, Forest Service, and recreationists) came together with the goal of protecting fisheries on the Blackfoot River. This group has been very effective at improving river conditions through conservation easements, changes in cattle-ranching
practices, and self-imposed recreation restrictions on portions of the river. The value of the river brought people together to protect this resource that also provided a sport-fishing site for visitors from around the world. On the other hand, some laws recently passed in Montana have had negative affects on nonresident fishing visitors. Local residents concerned about too many nonresidents fishing on the Big Hole and Beaverhead Rivers in southwestern Montana convinced the Montana Fish, Wildlife and Parks Commission (2005) to regulate nonresident fishing times on the river, which affected both outfitters and independent fishermen. Data presented here suggest that nonresident fishing makes a substantial economic contribution to the state of Montana. Policy makers should be aware of this and encourage preservation of these valuable resources, and at the same time, provide reasonable access. While fishing visitors have the highest per-day expenditures, where these visitors spend their money is even more interesting. On average, fishing visitors spend $30.32 a day on outfitters or guides, which is 135% more than the next highest visitor spending on outfitters on those same services. Outfitters and guides are local entrepreneurs who typically spend their money locally, thereby reducing leakage to outside areas. It is this type of tourism income that most states often encourage because of the local benefit. From a marketing perspective, Montana would not have to promote masses of nonresident fishing visitors to see increased economic benefit. By doubling this small group of visitors (currently at 4%), the total direct expenditures would be higher than all the other attractions to the state, yet it would still be a smaller number of visitors than five of the top six attractions to the state. However, when use of a resource is promoted, an inventory and sustainable audit is recommended. The state travel-marketing organization and the state Department of Fish, Wildlife, and Parks need to agree
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*Delimited to 30 nights.
Sample size (N = 2819) Percent of population Gas Retail sales Restaurant, bar Hotel, lodge, B&B Groceries Auto rental, repairs Outfitter, guide Licenses, entrance fees Campground, RV park Transportation fares Miscellaneous expenses, services Total average daily per group Average length of stay* Average trip expenditures Total direct expenditures of sample 326 12% $26.52 $41.64 $34.65 $20.82 $9.30 $3.03 $1.28 $3.32 $1.98 $0.00 $3.95 $146.49 5.53 $810.09 $264,000
$176.29 9.31 $1,641.26 $195,000
Open Space
119 4% $26.88 $29.67 $26.22 $15.98 $17.48 $13.68 $30.32 $10.05 $2.10 $0.00 $3.90
Fishing
$139.56 3.02 $421.47 $247,000
586 21% $29.25 $25.59 $29.48 $27.75 $11.04 $3.47 $2.35 $5.81 $3.09 $0.11 $1.63
Yellowstone Park
$130.23 6.29 $819.15 $384,000
469 17% $27.17 $25.27 $23.19 $18.46 $12.47 $5.86 $6.91 $3.58 $5.45 $0.30 $1.58
Glacier Park
$128.75 4.12 $530.45 $73,000
138 5% $30.47 $28.39 $28.15 $20.62 $7.37 $4.37 $0.00 $4.57 $4.09 $0.00 $0.73
History & Culture
$125.09 6.32 $790.57 $291,000
368 13% $23.65 $37.35 $23.57 $12.65 $10.75 $8.23 $2.77 $2.53 $1.41 $0.00 $2.18
Friends & Relatives
AVERAGE DAILY EXPENDITURES BY TOP NINE MAIN ATTRACTIONS TO MONTANA
TABLE 3
$122.99 6.80 $836.33 $127,000
152 5% $29.98 $18.61 $22.12 $15.72 $10.10 $4.77 $12.87 $6.66 $1.48 $0.00 $0.67
Hunting
$122.85 5.65 $694.10 $206,000
297 11% $26.59 $21.49 $24.49 $25.98 $9.61 $4.14 $3.77 $3.62 $1.89 $0.00 $1.28
Mountains
$106.85 6.07 $648.58 $80,000
123 4% $30.13 $27.29 $20.48 $15.15 $6.00 $3.95 $0.44 $1.32 $1.28 $0.12 $0.69
Special Event
JOURNAL OF TRAVEL RESEARCH 23 TABLE 4 VACATIONERS’ AVERAGE DAILY EXPENDITURES OF FIRST-TIME OR REPEAT VISITORS AND VISITORS WITH OR WITHOUT CHILDREN Vacationer Vacationer Vacationer No Children Repeat Visitors First-Time Visitors Younger than 18 Sample size Percent of population Gas Retail sales Restaurant, bar Hotel, lodge, B&B Groceries Auto rental, repairs Outfitter, guide Licenses, entrance fees Campground, RV park Transportation fares Miscellaneous expenses, services Total average daily per group Average length of stay* Average trip expenditures Total direct expenditures of sample
1,277 72% $27.29 $32.70 $29.66 $21.48 $13.56 $5.31 $8.61 $5.27 $3.10 $0.05 $2.58 $149.62 6.17 $923.16 $1.2 mil.
495 28% $26.57 $27.91 $27.24 $24.30 $9.57 $3.78 $5.07 $5.81 $4.32 $0.34 $1.32 $136.23 4.54 $618.48 $306,000
Vacationer with Children Younger than 18
1,316 75% $26.10 $29.89 $27.41 $21.18 $11.22 $5.09 $6.48 $5.33 $3.48 $0.15 $2.04 $138.37 6.13 $848.21 $1.1 mil.
447 25% $29.96 $35.66 $33.81 $25.58 $16.04 $4.33 $11.12 $5.99 $3.37 $0.11 $2.40 $168.37 4.65 $782.92 $350,000
*Delimited to 30 nights.
TABLE 5 VACATIONERS’ MAIN ATTRACTION BY THEIR FIRST-TIME OR REPEAT VISIT TO THE STATE Visitor
Yellowstone Glacier National Park National Park Mountains Open Space History/Culture Special Event Fishing Hunting VFR
First time
34%
24%
9%
9%
4%
3%
2%
2%
5%
Repeat
16%
14%
11%
12%
5%
5%
5%
6%
14%
Note: VFR= visiting friends and relatives
jointly on the travel promotion message in regard to the amount, type, and fishing locations suggested to vacationers. Visitors attracted to Montana’s open space had the second highest daily expenditure and the fifth longest length of stay. Similar to policies related to fishing, the state needs to be aware of how open space can contribute to the economy. Population growth in western Montana has continued to surge since the early 1990s with agricultural lands’ being subdivided and developed, reducing the views of open space in many areas of the state, especially western Montana (Swanson, Nickerson, and Lathrop 2003). As described by Diamond (2005), Montanans are at a crossroads in terms of their natural-resource values. Montana needs to choose whether open space is of such value that laws and regulations should be enacted to protect what is valued and why people choose to live in Montana. Like the fishing policies brought out by the Blackfoot Challenge, protecting open space for residents likewise will protect that which attracts visitors to the state. Indeed, an increase of visitors who are attracted primarily to Montana’s open space place even less of an impact on the natural resources than that of nonresident fishing visitors. Therefore, from a marketing perspective, the open-space experience could be packaged to visitors while remaining a highly sustainable tourism commodity. The two national parks, Yellowstone and Glacier, are major draws for nonresident tourism in Montana. More
vacationers mentioned Yellowstone and Glacier as their primary attraction to the state (21% and 17% respectively) than any other attraction. Visitors who indicated Yellowstone as their primary attraction had the shortest length of stay of all attractions but the third highest daily expenditure. Visitors primarily attracted to Glacier stayed twice as long as the Yellowstone visitor but spent $9 less per day. This still makes the Glacier visitor more valuable economically than the Yellowstone visitor because of the length of stay. From a policy position, Montana should be an active player in the preservation and promotion of the parks and surrounding areas. Without continued public support of and interest in the two parks, nonresident tourism in Montana could decrease at a considerable rate—up to 38%, based on these data. The final two groups for natural-resource-based attractions were people primarily attracted to Montana for the hunting or the mountains. Visitors attracted by these two features spent nearly identical amounts of money per day ($122.99 vs. $122.85), but hunters stayed slightly longer (6.80 days compared to 5.65). However, only 5% of the visitors were hunters, whereas 11% were attracted to mountains. This indicates that mountain visitors contribute more economically to the state than nonresident hunters. However, like visitors attracted to fishing, hunters have the second longest length of stay, and therefore, spend more per visit. Hunting, like fishing, depends on natural resources
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AUGUST 2006
that need to be monitored systematically to keep those resources sustainable. Promotion and marketing of these activities will require awareness that development of these attractions is limited—fish and game resources are not an endless bounty. The natural-resource attractions of Montana, in total, represented 76% of the total nonresident tourism expenditures in the state. The remaining 24% comprised the three main attractions that were not natural-resource based—history and culture, visiting friends and relatives (VFR), and special events. Even though history and culture generated the highest per-day expenditure of those three attractions, these visitors also had the shortest length of stay, which amounts to the smallest direct expenditures of all nine attractions. Interestingly, visitors who were primarily attracted because of friends or relatives living in the state contributed the third highest total direct expenditures of all attractions. Special events turned out to have the second smallest total expenditures from nonresident visitors. From a marketing perspective, the VFR group is strong in the state, and therefore, a continuation of the invitea-friend campaign (VisitMT 2005) is recommended. Finally, interesting results emerged when looking at the average daily expenditures of repeat visitors or first-time visitors and visitors with or without children (Table 4). Marketing decisions related to Montana tourism should examine their policy of seeking repeat visitors (which is an easier and generally less expensive approach) or pursuing first-time visitors. First-time visitors to Montana are more likely to be attracted to the state because of Yellowstone or Glacier National Parks (Table 5). Marketing promotions highlighting the two national parks will capture more firsttime visitors than those highlighting other attractions. From this perspective, marketers should target geographic areas that are not in the top 10 of Montana’s visitors (Nickerson 2003; Wilton 2004). This approach toward marketing may appeal to the first-timers and increase visitors from other states or areas not usually observed in Montana. Furthermore, because 72% of Montana’s vacationers are repeat visitors to the state, it appears that once they have visited, they likely will return. Keeping this in perspective, however, repeat visitors spend nearly 2 days longer than first-time visitors, which should cause marketers to step back and look at the value and cost of targeting first-time visitors. Nevertheless, looking at the data further showed that more than half (54%) of first-time vacationers plan to visit again within 2 years. It appears, then, that targeting first-time vacationers turns these visitors into future visitors within the following 2 years, which seems to be a fairly good investment. Segmenting by vacationers with or without children may not be a recommend marketing strategy for the state. Even though visitors with children spend $30 per day more, they only represent 25% of the vacation market, and their length of stay is nearly 2 days shorter. Economically, vacationers without children contribute substantially more than those with children.
Conclusion Visitor spending, when collected from the visitor with an onsite diary method or other methodology that minimizes recall bias, can produce detailed accounts of individual spending patterns and daily expenditures that can be analyzed further
and used for policy and marketing. Through this analysis of visitor spending based on the primary attraction to Montana, perhaps the most compelling finding was the relationship between Montana’s natural-resource attractions and visitor spending. Fishing, open space, national parks, mountains, and hunting are the primary features for nonresident visitors, which then lead to the largest share of nonresident spending in Montana as well. Without these attractions, the tourism sector would not be of the same significance. Furthermore, with Montana residents being fairly supportive of and dependent on tourism in the state (Wilton 2005), potential decreases in visitation could cause considerable local concern. In Lost Landscapes and Failed Economies (1996), Thomas Power, who is not a believer that a state’s economy should be based solely on tourism, suggests that tourism can be a part of the economy while still preserving the reason (i.e., natural resources) why people live in Montana. He states, “The primary economic contribution of protected landscapes and communities is attracting not tourists but rather permanent residents and businesses, which stimulate and support diverse economic activity. But tourism can be part of the economic mix without poisoning it” (p. 233). Similarly, Diamond (2005) suggests that Montanans are poised either to save that for which they live here (scenery, open space, beautiful landscapes) or compromise the landscape through resource extraction and overdevelopment. This article is one argument for the preservation of the landscape based on nonresident visitor preferences for Montana’s natural resources and the spending attributed to it.
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