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It has been updated to reflect current practices and to situate ITRR's approach within the broader tourism research literature, including recent advances in digital data collection and big-data methods. ) /Pg 9 0 R /K [5] >> endobj 95 0 obj << /Type /StructElem /S /H3 /P 79 0 R /T (SURVEY POPULATION ) /E (SURVEY POPULATION ) /Pg 9 0 R /K [6] >> endobj 96 0 obj << /Type /StructElem /S /P /P 79 0 R /E (The population of interest is all nonresident travelers in Թ, encompassing both domestic \(out-of-state\) and international visitors. Residents of Թ are excluded from the survey population. This scope is consistent with standard definitions used by national tourism research bodies such as the U.S. Travel Association and the National Travel and Tourism Office \(NTTO\), which define nonresident or inbound travelers as individuals whose place of permanent residence is outside the destination region \(NTTO, 2024\). ) /Pg 9 0 R /K [7] >> endobj 97 0 obj << /Type /StructElem /S /H3 /P 79 0 R /T (SAMPLING SCHEDULE & LOCATIONS ) /E (SAMPLING SCHEDULE & LOCATIONS ) /Pg 9 0 R /K [8] >> endobj 98 0 obj << /Type /StructElem /S /P /P 79 0 R /E <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> /Pg 9 0 R /K [9] >> endobj 99 0 obj << /Type /StructElem /S /Figure /P 79 0 R /Pg 9 0 R /A [354 0 R 0] /K [10] >> endobj 100 0 obj << /Type /StructElem /S /P /P 80 0 R /E <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> /Pg 10 0 R /K [0] >> endobj 101 0 obj << /Type /StructElem /S /P /P 80 0 R /E (Communities and sites currently included in the sampling frame are organized by region: ) /Pg 10 0 R /K [1] >> endobj 102 0 obj << /Type /StructElem /S /P /P 355 0 R /E (Airports: Billings, Bozeman, Great Falls, Helena, Kalispell, Missoula ) /Pg 10 0 R /K [2] >> endobj 103 0 obj << /Type /StructElem /S /P /P 356 0 R /E (Kalispell area: Kalispell, West Glacier, Hungry Horse, Columbia Falls, Whitefish, Polson, Libby, Eureka, Bigfork, Troy, Creston ) /Pg 10 0 R /K [3] >> endobj 104 0 obj << /Type /StructElem /S /P /P 357 0 R /E (Missoula area: Missoula, Bonner, Frenchtown Wye, Lolo, Hamilton, St. Regis, Thompson Falls ) /Pg 10 0 R /K [4] >> endobj 105 0 obj << /Type /StructElem /S /P /P 358 0 R /E (Dillon area: Dillon, Rocker, rest area along I-15, Anaconda, Butte, Lima ) /Pg 10 0 R /K [5] >> endobj 106 0 obj << /Type /StructElem /S /P /P 359 0 R /E (Shelby area: Shelby, Cut Bank, St. Mary, Havre, Browning, East Glacier ) /Pg 10 0 R /K [6] >> endobj 107 0 obj << /Type /StructElem /S /P /P 360 0 R /E (Great Falls area: Great Falls, Helena, Lewistown, White Sulphur Springs, Townsend ) /Pg 10 0 R /K [7] >> endobj 108 0 obj << /Type /StructElem /S /P /P 361 0 R /E (Bozeman area: Bozeman, Belgrade, Four Corners, Big Sky, West Yellowstone, Ennis, Three Forks, Livingston, Gardiner, Big Timber, Harlowton, Whitehall ) /Pg 10 0 R /K [8] >> endobj 109 0 obj << /Type /StructElem /S /P /P 362 0 R /E (Billings area: Billings, Crow Agency, Red Lodge, Columbus, Hardin, Laurel, Broadus ) /Pg 10 0 R /K [9] >> endobj 110 0 obj << /Type /StructElem /S /P /P 363 0 R /E (Missouri River area: Culbertson, Glasgow, Plentywood, Malta, Chinook, Wolf Point ) /Pg 10 0 R /K [10] >> endobj 111 0 obj << /Type /StructElem /S /P /P 364 0 R /E (Southeast MT area: Glendive, Miles City, Sidney, Circle. The sampling frame may be expanded or reduced if data analysis identifies a need for greater geographic diversity or if data volume at a given site is insufficient to justify continued surveyor deployment. ) /Pg 10 0 R /K [11] >> endobj 112 0 obj << /Type /StructElem /S /P /P 80 0 R /E (Proportion Counts: To collect a proportion of resident to nonresident traffic, both highway and airport counts are obtained year-round. Highway proportion counts are conducted at 21 border points through vehicle license plate observation during daylight hours, using a randomized schedule of days and times. Airport proportion counts are obtained by interviewing boarding passengers at Թ's six commercial airports, with counts randomized across airlines, days, and times of day. ) /Pg 10 0 R /K [12] >> endobj 113 0 obj << /Type /StructElem /S /H1 /P 80 0 R /T (VISITOR COUNTING & SPENDING ESTIMATION: A PROCESS OVERVIEW ) /E (VISITOR COUNTING & SPENDING ESTIMATION: A PROCESS OVERVIEW ) /Pg 10 0 R /K [13] >> endobj 114 0 obj << /Type /StructElem /S /P /P 80 0 R /E (The figure on the following page illustrates how ITRR combines primary survey data with secondary administrative data sources to produce estimates of total nonresident visitation and travel spending in Թ. ) /Pg 10 0 R /K [14] >> endobj 115 0 obj << /Type /StructElem /S /Figure /P 80 0 R /Pg 10 0 R /A [365 0 R 0] /K [15] >> endobj 116 0 obj << /Type /StructElem /S /H4 /P 81 0 R /T (Highway Proportion Counts) /E (Highway Proportion Counts) /Pg 11 0 R /K [0] >> endobj 117 0 obj << /Type /StructElem /S /P /P 81 0 R /E (21 border points; license plate observations) /Pg 11 0 R /K [1] >> endobj 118 0 obj << /Type /StructElem /S /H4 /P 81 0 R /T (Airport Proportion Counts) /E (Airport Proportion Counts) /Pg 11 0 R /K [2] >> endobj 119 0 obj << /Type /StructElem /S /P /P 81 0 R /E (6 MT airports; boarding passenger interviews) /Pg 11 0 R /K [3] >> endobj 120 0 obj << /Type /StructElem /S /H4 /P 81 0 R /T (DOT Traffic Counts) /E (DOT Traffic Counts) /Pg 11 0 R /K [4] >> endobj 121 0 obj << /Type /StructElem /S /P /P 81 0 R /E (MT, ND, WY, ID Depts of Transportation) /Pg 11 0 R /K [5] >> endobj 122 0 obj << /Type /StructElem /S /H4 /P 81 0 R /T (Average Daily Group Spending) /E (Average Daily Group Spending) /Pg 11 0 R /K [6] >> endobj 123 0 obj << /Type /StructElem /S /P /P 81 0 R /E (\(from intercept surveys\)) /Pg 11 0 R /K [7] >> endobj 124 0 obj << /Type /StructElem /S /H4 /P 81 0 R /T (Total Visitor Groups) /E (Total Visitor Groups) /Pg 11 0 R /K [8] >> endobj 125 0 obj << /Type /StructElem /S /P /P 81 0 R /E (\(from Step 3\)) /Pg 11 0 R /K [9] >> endobj 126 0 obj << /Type /StructElem /S /H2 /P 81 0 R /T (STEP 4: TOTAL SPENDING ESTIMATE) /E (STEP 4: TOTAL SPENDING ESTIMATE) /Pg 11 0 R /K [10] >> endobj 127 0 obj << /Type /StructElem /S /H4 /P 81 0 R /T (Average Length of Stay) /E (Average Length of Stay) /Pg 11 0 R /K [11] >> endobj 128 0 obj << /Type /StructElem /S /P /P 81 0 R /E (\(nights in MT\)) /Pg 11 0 R /K [12] >> endobj 129 0 obj << /Type /StructElem /S /H3 /P 81 0 R /T (TOTAL SPENDING ENTERED INTO IMPLAN MODEL ) /E (TOTAL SPENDING ENTERED INTO IMPLAN MODEL ) /Pg 11 0 R /K [13] >> endobj 130 0 obj << /Type /StructElem /S /H3 /P 81 0 R /T (JOBS, LABOR INCOME, AND ECONOMIC OUTPUT FOR MT) /E (JOBS, LABOR INCOME, AND ECONOMIC OUTPUT FOR MT) /Pg 11 0 R /K [14] >> endobj 131 0 obj << /Type /StructElem /S /H1 /P 81 0 R /T (HOW ITRR ESTIMATES NONRESIDENT VISITATION TO MONTANA) /E (HOW ITRR ESTIMATES NONRESIDENT VISITATION TO MONTANA) /Pg 11 0 R /K [15] >> endobj 132 0 obj << /Type /StructElem /S /H2 /P 81 0 R /T (STEP 1: DATA INPUTS) /E (STEP 1: DATA INPUTS) /Pg 11 0 R /K [16] >> endobj 133 0 obj << /Type /StructElem /S /H4 /P 81 0 R /T (Border Crossing Data) /E (Border Crossing Data) /Pg 11 0 R /K [17] >> endobj 134 0 obj << /Type /StructElem /S /P /P 81 0 R /E (U.S. Customs & ) /Pg 11 0 R /K [18] >> endobj 135 0 obj << /Type /StructElem /S /P /P 81 0 R /E (Border Protection ) /Pg 11 0 R /K [19] >> endobj 136 0 obj << /Type /StructElem /S /P /P 81 0 R /E (\(12 sites\)) /Pg 11 0 R /K [20] >> endobj 137 0 obj << /Type /StructElem /S /H2 /P 81 0 R /T (STEP 2: CALCULATE NONRESIDENT %) /E (STEP 2: CALCULATE NONRESIDENT %) /Pg 11 0 R /K [21] >> endobj 138 0 obj << /Type /StructElem /S /H3 /P 81 0 R /T (PROPORTION COUNTS AT HIGHWAYS AND AIRPORTS DETERMINE THE PERCENTAGE OF VEHICLES/PASSENGERS THAT ARE NONRESIDENTS VS. MONTANA RESIDENTS) /E (PROPORTION COUNTS AT HIGHWAYS AND AIRPORTS DETERMINE THE PERCENTAGE OF VEHICLES/PASSENGERS THAT ARE NONRESIDENTS VS. MONTANA RESIDENTS) /Pg 11 0 R /K [22] >> endobj 139 0 obj << /Type /StructElem /S /H2 /P 81 0 R /T (STEP 3: VISITATION ESTIMATION FORMULA) /E (STEP 3: VISITATION ESTIMATION FORMULA) /Pg 11 0 R /K [23] >> endobj 140 0 obj << /Type /StructElem /S /H3 /P 81 0 R /T (TOTAL VEHICLES ENTERING MT X NONRESIDENT % X AVERAGE GROUP SIZE = TOTAL NONRESIDENT TRAVELERS) /E (TOTAL VEHICLES ENTERING MT X NONRESIDENT % X AVERAGE GROUP SIZE = TOTAL NONRESIDENT TRAVELERS) /Pg 11 0 R /K [24] >> endobj 141 0 obj << /Type /StructElem /S /H2 /P 81 0 R /T (STEP 5: ECONOMIC IMPACT ANALYSIS) /E (STEP 5: ECONOMIC IMPACT ANALYSIS) /Pg 11 0 R /K [25] >> endobj 142 0 obj << /Type /StructElem /S /H5 /P 81 0 R /T ( Figure 1. ITRR Nonresident Visitation & Spending Estimation Process) /E ( Figure 1. ITRR Nonresident Visitation & Spending Estimation Process) /Pg 11 0 R /K [26] >> endobj 143 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [366 0 R 0] /K [27] >> endobj 144 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [367 0 R 0] /K [28] >> endobj 145 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [368 0 R 0] /K [29] >> endobj 146 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [369 0 R 0] /K [30] >> endobj 147 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [370 0 R 0] /K [31] >> endobj 148 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [371 0 R 0] /K [32] >> endobj 149 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [372 0 R 0] /K [33] >> endobj 150 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [373 0 R 0] /K [34] >> endobj 151 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [374 0 R 0] /K [35] >> endobj 152 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [375 0 R 0] /K [36] >> endobj 153 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [376 0 R 0] /K [37] >> endobj 154 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [377 0 R 0] /K [38] >> endobj 155 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [378 0 R 0] /K [39] >> endobj 156 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [379 0 R 0] /K [40] >> endobj 157 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [380 0 R 0] /K [41] >> endobj 158 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [381 0 R 0] /K [42] >> endobj 159 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [382 0 R 0] /K [43] >> endobj 160 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [383 0 R 0] /K [44] >> endobj 161 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [384 0 R 0] /K [45] >> endobj 162 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [385 0 R 0] /K [46] >> endobj 163 0 obj << /Type /StructElem /S /Figure /P 81 0 R /Pg 11 0 R /A [386 0 R 0] /K [47] >> endobj 164 0 obj << /Type /StructElem /S /H1 /P 82 0 R /T (DATA COLLECTION METHODS) /E (DATA COLLECTION METHODS) /Pg 12 0 R /K [0] >> endobj 165 0 obj << /Type /StructElem /S /P /P 82 0 R /E (ITRR employs two complementary survey instruments administered sequentially to the same respondent pool. ) /Pg 12 0 R /K [1] >> endobj 166 0 obj << /Type /StructElem /S /H2 /P 82 0 R /T (ON-SITE INTERCEPT SURVEY ) /E (ON-SITE INTERCEPT SURVEY ) /Pg 12 0 R /K [2] >> endobj 167 0 obj << /Type /StructElem /S /P /P 82 0 R /E (Surveyors approach travelers at gas stations, rest areas, and airports to determine eligibility \(i.e., non-Թ residency\) and administer the on-site survey using iPads via the iForm application. The on-site instrument collects: ) /Pg 12 0 R /K [3] >> endobj 168 0 obj << /Type /StructElem /S /P /P 387 0 R /E (Mode of travel and travel group type and size ) /Pg 12 0 R /K [4] >> endobj 169 0 obj << /Type /StructElem /S /P /P 388 0 R /E (State, province, or country of permanent residence and U.S. zip/postal code ) /Pg 12 0 R /K [5] >> endobj 170 0 obj << /Type /StructElem /S /P /P 389 0 R /E (Purpose of trip \(all applicable purposes and single main purpose\) ) /Pg 12 0 R /K [6] >> endobj 171 0 obj << /Type /StructElem /S /P /P 390 0 R /E (Point of entry into Թ ) /Pg 12 0 R /K [7] >> endobj 172 0 obj << /Type /StructElem /S /P /P 391 0 R /E (Number of nights already spent and planned in Թ ) /Pg 12 0 R /K [8] >> endobj 173 0 obj << /Type /StructElem /S /P /P 392 0 R /E (Expenditures during a 24-hour period, recorded by category and location \(town/county\) ) /Pg 12 0 R /K [9] >> endobj 174 0 obj << /Type /StructElem /S /P /P 82 0 R /E (The on-site survey also captures accommodation type \(including short-term rental platforms such as Airbnb and VRBO, which were added to reflect the significant growth in platform-mediated lodging since 2010\) and reservation method. This addition aligns ITRR's instrument with national best-practice guidelines for accommodation tracking, as platform-based stays now represent a substantial and growing share of visitor nights in many destinations \(Guttentag, 2019; UNWTO, 2020\). ) /Pg 12 0 R /K [10] >> endobj 175 0 obj << /Type /StructElem /S /H2 /P 82 0 R /T (FOLLOW-UP MAIL/ONLINE SURVEY ) /E (FOLLOW-UP MAIL/ONLINE SURVEY ) /Pg 12 0 R /K [11] >> endobj 176 0 obj << /Type /StructElem /S /P /P 82 0 R /E (Upon completion of the on-site survey, respondents are invited to participate in a more extensive follow-up survey, distributed via a pre-addressed, postage-paid reply envelope containing a paper form, an introductory letter, and information on the quarterly incentive drawing \(10 winners of $100 prize\). Respondents may also complete the survey online. The follow-up instrument collects data on: ) /Pg 12 0 R /K [12] >> endobj 177 0 obj << /Type /StructElem /S /P /P 393 0 R /E (Routes driven within Թ and sites visited ) /Pg 12 0 R /K [13] >> endobj 178 0 obj << /Type /StructElem /S /P /P 394 0 R /E (Activities participated in ) /Pg 12 0 R /K [14] >> endobj 179 0 obj << /Type /StructElem /S /P /P 395 0 R /E (Pre-trip and in-trip information sources used ) /Pg 12 0 R /K [15] >> endobj 180 0 obj << /Type /StructElem /S /P /P 396 0 R /E (Satisfaction ratings across multiple dimensions of the Թ visitor experience ) /Pg 12 0 R /K [16] >> endobj 181 0 obj << /Type /StructElem /S /P /P 397 0 R /E (Demographic information \(age, gender, household income\) ) /Pg 12 0 R /K [17] >> endobj 182 0 obj << /Type /StructElem /S /P /P 398 0 R /E (Lodging location and type for each night of the trip \(up to 8 nights\) ) /Pg 12 0 R /K [18] >> endobj 183 0 obj << /Type /StructElem /S /P /P 399 0 R /E (Whether the respondent used a commercial air carrier for any portion of the trip, own a 2nd property in the state, or hired an outfitter/guide ) /Pg 12 0 R /K [19] >> endobj 184 0 obj << /Type /StructElem /S /P /P 82 0 R /E (A unique survey ID links each respondent's on-site and follow-up records, enabling data merging for a more complete picture of traveler characteristics and experiences while maintaining respondent confidentiality. ) /Pg 12 0 R /K [20] >> endobj 185 0 obj << /Type /StructElem /S /H1 /P 83 0 R /T (WORKING WITH THE NONRESIDENT TRAVEL DATA ) /E (WORKING WITH THE NONRESIDENT TRAVEL DATA ) /Pg 13 0 R /K [0] >> endobj 186 0 obj << /Type /StructElem /S /H2 /P 83 0 R /T (MERGING THE TWO DATA SETS ) /E (MERGING THE TWO DATA SETS ) /Pg 13 0 R /K [1] >> endobj 187 0 obj << /Type /StructElem /S /P /P 83 0 R /E (Data from both survey instruments are cleaned and coded prior to analysis. The unique ID number printed on each follow-up survey and envelope allows on-site records to be matched with corresponding follow-up records. During data cleaning, values for variables such as length of stay are delimited to prevent extreme outliers from distorting estimates. Merging the two data sets produces a richer profile of each respondent's trip characteristics and spending behavior. ) /Pg 13 0 R /K [2] >> endobj 188 0 obj << /Type /StructElem /S /H2 /P 83 0 R /T (WEIGHTING ) /E (WEIGHTING ) /Pg 13 0 R /K [3] >> endobj 189 0 obj << /Type /StructElem /S /P /P 83 0 R /E (To ensure that the survey sample is representative of the full population of nonresident travelers, data are weighted in two ways: ) /Pg 13 0 R /K [4] >> endobj 190 0 obj << /Type /StructElem /S /P /P 400 0 R /E (By entry point into Թ: ) /Pg 13 0 R /K [5] >> endobj 191 0 obj << /Type /StructElem /S /P /P 401 0 R /E (Adjusts for proportional disparities between where vehicles enter the state and where surveys were collected. This corrects for any geographic clustering in surveyor deployment. ) /Pg 13 0 R /K [6] >> endobj 192 0 obj << /Type /StructElem /S /P /P 402 0 R /E (By trip purpose: ) /Pg 13 0 R /K [7] >> endobj 193 0 obj << /Type /StructElem /S /P /P 403 0 R /E (Adjusts for differences in trip purpose distributions between on-site and follow-up respondents. Because not all on-site participants complete the follow-up survey, weighting the follow-up data to match the on-site distribution ensures the merged data set represents the full population of travelers. ) /Pg 13 0 R /K [8] >> endobj 194 0 obj << /Type /StructElem /S /P /P 83 0 R /E <546865736520776569676874696E6720617070726F61636865732061726520636F6E73697374656E7420776974682065737461626C697368656420707261637469636520696E20746F757269736D20737572766579206D6574686F646F6C6F677920284672656368746C696E672C20323030363B20536561746F6E20262042656E6E6574742C20313939362920616E6420616464726573732077656C6C2D646F63756D656E74656420636F6E6365726E732061626F7574206E6F6E2D726573706F6E7365206269617320696E20696E7465726365707420737572766579732028446F6C6E696361722026204772FC6E2C2032303231292E20> /Pg 13 0 R /K [9] >> endobj 195 0 obj << /Type /StructElem /S /H2 /P 83 0 R /T (EXPENDITURE DATA ) /E (EXPENDITURE DATA ) /Pg 13 0 R /K [10] >> endobj 196 0 obj << /Type /StructElem /S /P /P 83 0 R /E (The on-site survey captures each visitor group's 24-hour spending in Թ, disaggregated by expenditure category \(e.g., accommodation, gasoline, restaurants, groceries, retail goods, guided trips, licenses/admissions, and entertainment\). For each category, the location of the expenditure is recorded and subsequently coded by county and tourism region, enabling regional economic analysis. ) /Pg 13 0 R /K [11] >> endobj 197 0 obj << /Type /StructElem /S /P /P 83 0 R /E (Expenditure data are delimited to prevent outliers from inflating category means: any value exceeding three standard deviations above the mean is reduced to that threshold. For accommodation categories, an additional adjustment is made based on bed tax collections to improve accuracy \(A 4% Lodging Facility Use Tax was established in 1987 and a 3% Lodging Sales Tax enacted in 2003 and updated in 2019 to 4%. Together, these create an 8% statewide tax on lodging\). The means across all expenditure categories are summed to yield average daily spending per visitor group. This figure is combined with the visitation estimate and average length of stay to produce the total statewide nonresident travel spending estimate. ) /Pg 13 0 R /K [12] >> endobj 198 0 obj << /Type /StructElem /S /P /P 84 0 R /E (Note on Short-Term Rentals: The growth of platform-mediated lodging \(Airbnb, VRBO/HomeAway\) since 2010 has introduced new complexity into accommodation tracking and expenditure estimation. ITRR's survey instruments now explicitly capture platform-based stays and reservation methods, and the bed-tax adjustment methodology accounts for the differential tax treatment of short-term rentals in Թ.) /Pg 14 0 R /K [0] >> endobj 199 0 obj << /Type /StructElem /S /H1 /P 84 0 R /T (NONRESIDENT VISITATION ESTIMATION MODEL ) /E (NONRESIDENT VISITATION ESTIMATION MODEL ) /Pg 14 0 R /K [1] >> endobj 200 0 obj << /Type /StructElem /S /P /P 84 0 R /E (ITRR produces an annual estimate of the total volume of nonresident travelers and travel parties entering Թ. The model integrates both primary and secondary data sources: ) /Pg 14 0 R /K [2] >> endobj 201 0 obj << /Type /StructElem /S /P /P 404 0 R /E (Primary data: Proportion counts \(highway and airport\) and average group size from survey data ) /Pg 14 0 R /K [3] >> endobj 202 0 obj << /Type /StructElem /S /P /P 405 0 R /E (Secondary data: Airport deboardings from eight Թ commercial airports; traffic counts from the Թ, North Dakota, Wyoming, and Idaho Departments of Transportation; and international border crossing data from U.S. Customs and Border Protection \(12 count sites\) ) /Pg 14 0 R /K [4] >> endobj 203 0 obj << /Type /StructElem /S /P /P 84 0 R /E (Various adjustments within the model account for factors such as monthly traffic fluctuations \(in cases where only annual traffic counts are available\) and the multiple entries into Թ that occur for travelers visiting Yellowstone National Park via the northern entrances. ) /Pg 14 0 R /K [5] >> endobj 204 0 obj << /Type /StructElem /S /P /P 84 0 R /E (The core estimation formula is: ) /Pg 14 0 R /K [6] >> endobj 205 0 obj << /Type /StructElem /S /H3 /P 84 0 R /T <4E554D424552204F462056454849434C455320454E544552494E47204D5420D7204E4F4E5245534944454E54202520D720415645524147452047524F55502053495A45203D2020544F54414C204E4F4E5245534944454E542054524156454C45525320> /E <4E554D424552204F462056454849434C455320454E544552494E47204D5420D7204E4F4E5245534944454E54202520D720415645524147452047524F55502053495A45203D2020544F54414C204E4F4E5245534944454E542054524156454C45525320> /Pg 14 0 R /K [7] >> endobj 206 0 obj << /Type /StructElem /S /P /P 84 0 R /E (This approach is analogous to models used by state tourism offices across the country and by the National Park Service for estimating gateway community visitation \(Flyr & Koontz, 2023; NPS, 2022\). ) /Pg 14 0 R /K [8] >> endobj 207 0 obj << /Type /StructElem /S /H2 /P 84 0 R /T (EMERGING SUPPLEMENTAL METHODS: PASSIVE MOBILE DEVICE DATA ) /E (EMERGING SUPPLEMENTAL METHODS: PASSIVE MOBILE DEVICE DATA ) /Pg 14 0 R /K [9] >> endobj 208 0 obj << /Type /StructElem /S /P /P 84 0 R /E <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> /Pg 14 0 R /K [10] >> endobj 209 0 obj << /Type /StructElem /S /Figure /P 84 0 R /Pg 14 0 R /A [406 0 R 0] /K [11] >> endobj 210 0 obj << /Type /StructElem /S /Figure /P 84 0 R /Pg 14 0 R /A [407 0 R 0] /K [12] >> endobj 211 0 obj << /Type /StructElem /S /P /P 85 0 R /E (However, passive mobile data have recognized limitations: they cannot capture qualitative visitor characteristics such as trip purpose, satisfaction, activities, or spending behavior; they are subject to demographic sampling biases \(reflecting device ownership patterns\); and they require careful calibration against ground-truth counts \(Baird et al., 2022; Monz et al., 2019\). For these reasons, ITRR's primary estimation methodology remains intercept-survey based, while the tourism research community continues to evaluate the conditions under which mobile data can validly supplement traditional methods. ) /Pg 15 0 R /K [0] >> endobj 212 0 obj << /Type /StructElem /S /H1 /P 85 0 R /T (ESTIMATING STATEWIDE NONRESIDENT TRAVEL SPENDING ) /E (ESTIMATING STATEWIDE NONRESIDENT TRAVEL SPENDING ) /Pg 15 0 R /K [1] >> endobj 213 0 obj << /Type /StructElem /S /P /P 85 0 R /E (Once survey expenditure data analysis is complete and visitation estimates have been finalized, ITRR calculates the total statewide nonresident travel spending using the following formula: ) /Pg 15 0 R /K [2] >> endobj 214 0 obj << /Type /StructElem /S /H2 /P 85 0 R /T <4156472E204441494C592047524F5550205350454E44494E4720D7204156472E204C454E475448204F46205354415920D720544F54414C2056495349544F522047524F555053203D20544F54414C204D54204E4F4E5245534944454E542054524156454C205350454E44494E4720> /E <4156472E204441494C592047524F5550205350454E44494E4720D7204156472E204C454E475448204F46205354415920D720544F54414C2056495349544F522047524F555053203D20544F54414C204D54204E4F4E5245534944454E542054524156454C205350454E44494E4720> /Pg 15 0 R /K [3] >> endobj 215 0 obj << /Type /StructElem /S /H1 /P 85 0 R /T (ECONOMIC CONTRIBUTION OF NONRESIDENT TRAVEL TO MONTANA ) /E (ECONOMIC CONTRIBUTION OF NONRESIDENT TRAVEL TO MONTANA ) /Pg 15 0 R /K [4] >> endobj 216 0 obj << /Type /StructElem /S /P /P 85 0 R /E (ITRR uses IMPLAN economic analysis software and state-specific data to translate visitor spending estimates into measures of economic impact, including direct, indirect, and induced effects on employment, labor income, value added, and business output. A Թ-specific IMPLAN model is constructed annually, and total nonresident spending in each expenditure category is allocated to the appropriate IMPLAN economic sector. ) /Pg 15 0 R /K [5] >> endobj 217 0 obj << /Type /StructElem /S /P /P 85 0 R /E (Several expenditure categories require close inspection to determine appropriate sectoral allocation and amounts. In addition to statewide estimates, ITRR produces county-level and travel-region-level spending and impact estimates for areas with sufficient data. ) /Pg 15 0 R /K [6] >> endobj 218 0 obj << /Type /StructElem /S /P /P 85 0 R /E (The IMPLAN approach is widely used in state and national park tourism impact analysis. For context, the National Park Service applies an analogous IMPLAN-based methodology to estimate that 312 million NPS recreation visits in 2022 generated approximately $23.9 billion in local gateway region spending, supporting an estimated 378,400 jobs nationally \(Flyr & Koontz, 2023\). ITRR's Թ-specific model applies similar sectoral logic to a state-level context. ) /Pg 15 0 R /K [7] >> endobj 219 0 obj << /Type /StructElem /S /Figure /P 85 0 R /Pg 15 0 R /A [408 0 R 0] /K [8] >> endobj 220 0 obj << /Type /StructElem /S /H1 /P 86 0 R /T (ACCESS TO AND USE OF NONRESIDENT TRAVEL DATA ) /E (ACCESS TO AND USE OF NONRESIDENT TRAVEL DATA ) /Pg 16 0 R /K [0] >> endobj 221 0 obj << /Type /StructElem /S /P /P 86 0 R /E (All nonresident travel data produced by ITRR are made available for public use through the Interactive Data portal on the ITRR homepage \(www.itrr.umt.edu\). Users can query data by quarter, and filter results by a variety of visitor and trip characteristics, including: ) /Pg 16 0 R /K [1] >> endobj 222 0 obj << /Type /StructElem /S /P /P 409 0 R /E (Visitors to specific Թ sites \(national parks, museums, historical landmarks, etc.\) as well as what attracted them to Թ ) /Pg 16 0 R /K [2] >> endobj 223 0 obj << /Type /StructElem /S /P /P 410 0 R /E (Visitors in specific age ranges ) /Pg 16 0 R /K [3] >> endobj 224 0 obj << /Type /StructElem /S /P /P 411 0 R /E (Entry mode \(car/truck, RV/trailer, airplane, motorcycle, bus, train, etc.\) ) /Pg 16 0 R /K [4] >> endobj 225 0 obj << /Type /StructElem /S /P /P 412 0 R /E (Activities participated in \(hiking, fishing, skiing, wildlife watching, etc.\) ) /Pg 16 0 R /K [5] >> endobj 226 0 obj << /Type /StructElem /S /P /P 86 0 R /E (Annual visitation and spending estimates are published on the ITRR website. The data are widely used by destination marketing organizations, tourism businesses, state and local policymakers, economic development agencies, and academic researchers. ITRR also publishes biennial reports on recreation participation and periodic special-topic research notes addressing emerging issues in Թ tourism. ) /Pg 16 0 R /K [6] >> endobj 227 0 obj << /Type /StructElem /S /H1 /P 87 0 R /T (SELECTED REFERENCES) /E (SELECTED REFERENCES) /Pg 17 0 R /K [0] >> endobj 228 0 obj << /Type /StructElem /S /P /P 87 0 R /E (Baird, T., Stinger, P., Cole, E., & Collins, R. \(2022\). Mobile device data for parks and public lands transportation planning: A framework for evaluation and applications. Transportation Research Record, 2676\(8\). https://doi.org/10.1177/03611981221083911 ) /Pg 17 0 R /K [1] >> endobj 229 0 obj << /Type /StructElem /S /P /P 87 0 R /E (Creany, N. E., Monz, C. A., D'Antonio, A., Sisneros-Kidd, A., Wilkins, E. J., Nesbitt, J., & Mitrovich, M. \(2021\). Estimating trail use and visitor spatial distribution using mobile device data: An example from the Nature Reserve of Orange County, California USA. Environmental Challenges, 4. https://doi.org/10.1016/j.envc.2021.100171 ) /Pg 17 0 R /K [2] >> endobj 230 0 obj << /Type /StructElem /S /P /P 87 0 R /E <446F6C6E696361722C20532E2C2026204772FC6E2C20422E202832303231292E2044657369676E696E6720746F757269736D207375727665797320746861742070726F6475636520616374696F6E61626C65206B6E6F776C656467652E204A6F75726E616C206F662054726176656C2052657365617263682C2036302831292C20338531342E20> /Pg 17 0 R /K [3] >> endobj 231 0 obj << /Type /StructElem /S /P /P 87 0 R /E <466C79722C204D2E2C2026204B6F6F6E747A2C204C2E202832303233292E2032303232204E6174696F6E616C205061726B2076697369746F72207370656E64696E6720656666656374733A2045636F6E6F6D696320636F6E747269627574696F6E7320746F206C6F63616C20636F6D6D756E69746965732C207374617465732C20616E6420746865206E6174696F6E2E204E61747572616C205265736F75726365205265706F7274204E50532F4E5253532F4551442F4E525284323032332F323535312E204E6174696F6E616C205061726B20536572766963652E20> /Pg 17 0 R /K [4] >> endobj 232 0 obj << /Type /StructElem /S /P /P 87 0 R /E <4672656368746C696E672C20442E20432E202832303036292E20416E206173736573736D656E74206F662076697369746F7220657870656E646974757265206D6574686F647320616E64206D6F64656C732E204A6F75726E616C206F662054726176656C2052657365617263682C2034352831292C2032368533352E20> /Pg 17 0 R /K [5] >> endobj 233 0 obj << /Type /StructElem /S /P /P 87 0 R /E <47757474656E7461672C20442E202832303139292E2050726F6772657373206F6E20416972626E623A2041206C697465726174757265207265766965772E204A6F75726E616C206F6620486F73706974616C69747920616E6420546F757269736D20546563686E6F6C6F67792C2031302834292C20383134853834342E20> /Pg 17 0 R /K [6] >> endobj 234 0 obj << /Type /StructElem /S /P /P 87 0 R /E (Monz, C., Mitrovich, M., D'Antonio, A., & Sisneros-Kidd, A. \(2019\). Using mobile device data to estimate visitation in parks and protected areas: An example from the Nature Reserve of Orange County, California. Journal of Park and Recreation Administration, 37\(4\). ) /Pg 17 0 R /K [7] >> endobj 235 0 obj << /Type /StructElem /S /P /P 87 0 R /E (National Park Service \(NPS\). \(2022\). 2022 National Park visitor spending effects. Fort Collins, CO: NPS. ) /Pg 17 0 R /K [8] >> endobj 236 0 obj << /Type /StructElem /S /P /P 87 0 R /E (National Travel and Tourism Office \(NTTO\). \(2024\). Survey of International Air Travelers. U.S. Department of Commerce. https://www.trade.gov/survey-international-air-travelers-siat ) /Pg 17 0 R /K [9] >> endobj 237 0 obj << /Type /StructElem /S /P /P 87 0 R /E <5261756E2C204A2E2C20416861732C20522E2C202620546972752C204D2E202832303136292E204D6561737572696E6720746F757269736D2064657374696E6174696F6E73207573696E67206D6F62696C6520747261636B696E6720646174612E20546F757269736D204D616E6167656D656E742C2035372C20323032853231322E20> /Pg 17 0 R /K [10] >> endobj 238 0 obj << /Type /StructElem /S /P /P 87 0 R /E <5363686DFC636B65722C20442E2C202620526569662C204A2E202832303232292E204D6561737572696E6720746F757269736D20776974682062696720646174613F20456D7069726963616C20696E7369676874732066726F6D20636F6D706172696E67207061737369766520475053206461746120616E642070617373697665206D6F62696C6520646174612E204A6F75726E616C206F6620546F757269736D20467574757265732C20382832292E20> /Pg 17 0 R /K [11] >> endobj 239 0 obj << /Type /StructElem /S /P /P 87 0 R /E (Seaton, A. V., & Bennett, M. M. \(1996\). The marketing of tourism products: Concepts, issues and cases. International Thomson Business Press.) /Pg 17 0 R /K [12] >> endobj 240 0 obj << /Type /StructElem /S /H1 /P 88 0 R /T <546965726E65792C20502E20542E202831393933292E20546865206C656973757265206D6F7469766174696F6E207175657374696F6E6E6169726520617320612072656372656174696F6E2064656D616E6420616E616C7973697320746F6F6C2E204A6F75726E616C206F66204C6569737572652052657365617263682C2032352831292C2037368539312E20> /E <546965726E65792C20502E20542E202831393933292E20546865206C656973757265206D6F7469766174696F6E207175657374696F6E6E6169726520617320612072656372656174696F6E2064656D616E6420616E616C7973697320746F6F6C2E204A6F75726E616C206F66204C6569737572652052657365617263682C2032352831292C2037368539312E20> /Pg 18 0 R /K [0] >> endobj 241 0 obj << /Type /StructElem /S /H1 /P 88 0 R /T (United Nations World Tourism Organization \(UNWTO\). \(2010\). International recommendations for tourism statistics 2008. 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