Factors Influencing Visitor's Choices of Urban Destinations in North ...

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Model 5B: Three-Star Quality-Rated Attractions, Room Count, and PopulationDensityDependent Variable: Total Number of Visits(Millions of Visitors)Sample: 2002Number of Observations: 50VariableCoefficientStd. ErrorT-StatConstant0.370.570.64Shopping Areas(Q3)0.610.173.66Amusement Parks (Q3)4.960.539.35Specific Structures (Q3)1.140.373.11# of Hotel Rooms0.0000910.000019.07Population Density0.080.0233.27Adj. R-sq0.90S.E. of Reg.1.57Source: Global Insight, Inc.Model 5C: Three-star Quality-Rated Attractions, Room Count and MarketingBudgetsDependent Variable: Total Number of Visits(Millions of Visitors)Sample: 2002Number of Observations: 33VariableCoefficientStd. ErrorT-StatConstant2.260.603.77Amusement Parks (Q3)4.520.627.25Specific Structures (Q3)1.020.462.21Shopping Areas(Q3)0.690.203.50Marketing Budgets0.100.052.24# of Hotel Rooms0.0000790.000024.15Adj. R-sq0.90S.E. of Reg.1.81Source: Global Insight, Inc.41
C. Literature ReviewTourism Attractiveness LiteratureTourism Attractiveness Literature focuses on a discussion of the range of factors thatinfluence the attractiveness of a destination. More formally, Leiper (1990) develops theidea of a tourist attraction system, comprised of “…3 elements: a tourist or humanelement, a nucleus or central element, and a marker or informative element. A touristattraction comes into existence when all 3 elements are connected.”“Culture as a Determinant of the Attractiveness of a Tourism Region”Ritchie and Zins (1978) examined factors that influence the overall attractiveness of atourism region and measured the relative contribution of different social and culturalelements to the attractiveness of a tourism region.A survey of 201 informed individuals representing a wide range of tourism and culturaldevelopment sectors was conducted in the province of Quebec. The results of this studysuggest that general factors such as natural beauty and climate were the most importantdeterminants of the attractiveness in the region followed in order by cultural and socialcharacteristics, attitudes towards tourists, accessibility of the region, infrastructure of theregion, price levels, sport/recreational facilities, and shopping/commercial facilities.One of the significant drawbacks 20 of this study is related to sample bias. The individualswho participated in this survey represented a particular group of tourism professionalsrather than users of culture-tourism facilities.“A Framework of Tourist Attraction Research”Lew (1987) summarizes a range of approaches from previous research to categorize theattractions. In particular, Lew identified three approaches to the topic and called theseapproaches the ideographic perspective, the organizational perspective, and the cognitiveperspective.1. The ideographic perspective refers to the general attributes of a place, includingnatural beauty, climate, culture, social customs, etc. The ideographic perspective does notprovide an assessment of quality of a particular attraction, quality of management, touristmotivation, and preference for different attraction. Moreover, there is no discussion ofspatial relationship between different locations.2. The organizational perspective does not necessarily examine the attractionsthemselves, bur rather focuses on spatial elements (i.e. in relation to other attractions),capacity to accommodate large number of tourists and provide with services (i.e. lodging,food, merchandise), and the temporal nature of attractions (a year-round flow of touristsvs. seasonal flow). Scale is used to categorize the spatial relationship of an attraction toother attractions. The bottom line of this approach is to provide insight into theorganization of tourist attractions.20 Pointed out by Zins (1978).42
Page 2 and 3: Table of ContentsI. EXECUTIVE SUMMA
Page 4 and 5: I. Executive SummaryHighlightsThe r
Page 6 and 7: Next StepsThis project has surfaced
Page 8 and 9: IV.coefficients from these models p
Page 10 and 11: series, simple autoregressive and
Page 12 and 13: Arts & Culture Museums Historymuseu
Page 14 and 15: The tourist visitations data was al
Page 16 and 17: Hotel Room Count and Hotel Property
Page 18 and 19: Table 9: Michelin’s RatingsRating
Page 20 and 21: value below one suggests that the s
Page 22 and 23: Table 13: Individual Attractions Th
Page 24 and 25: Table 16: Significant Results 14Equ
Page 26 and 27: The adjusted R 2 for this model is
Page 28 and 29: • On average across all cities, b
Page 30 and 31: Model 5C 17 : In Model 5C, the numb
Page 32 and 33: The model overpredicts the number o
Page 34 and 35: Attraction Elasticities for Ottawa
Page 36 and 37: Table 22: Marketing Budget Elastici
Page 38 and 39: VII.Technical AppendixA. Attraction
Page 40 and 41: • Metropolitan Opera House in New
Page 42 and 43: Model 3: Three-Star Quality-Rated A
Page 46 and 47: 3. The cognitive perspective involv
Page 48 and 49: also found that almost half of the
Page 50 and 51: Also, the model seems to completely
Page 52 and 53: strengths and its weaknesses, devel
Page 54 and 55: Items from QuestionnaireTable 23: M
Page 56 and 57: Tourism Demand/Econometric Modellin
Page 58 and 59: Table 25: Types of Explanatory Vari
Page 60 and 61: Results: Lim and McAleer found that
Page 62 and 63: Richards, Greg. (2002). “Tourism
Page 64 and 65: Figure 4: Overseas Visitors to U.S.
Page 66 and 67: Figure 6: Cities Person-Trips Volum

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