A MODEL OF THE U.S. OVERNIGHT HOLIDAY-VACATIONERS’ TRAVEL BEHAVIOUR IN CANADA Dongkoo Yun, Ph.D. School of Hospitality and Tourism Management University of Guelph Guelph, Ontario N1G 2W1 Canada Phone: 519.362.2110 Email:
[email protected] Marion Joppe, Ph.D. Director, Professor School of Hospitality and Tourism Management University of Guelph Guelph, Ontario N1G 2W1 Canada Phone: 519.824.4120 ext. 56118 Email:
[email protected]
A MODEL OF THE U.S. OVERNIGHT HOLIDAY-VACATIONERS’ TRAVEL BEHAVIOUR IN CANADA ABSTRACT The proposed model of the U.S. overnight holiday-vacationers’ travel behaviour was built by reviewing related literatures and information on the U.S. resident trips to Canada of the International Travel Survey (ITS) in 2004. In addition, the study examined the study model by rescaling the measures as tourism indices and performing LISREL estimation. An empirical test of the model provides support for the critical causal relationships between the constructs in the proposed model. Consequently, the study contributes to a better understanding of the U.S. holiday-vacationers’ market.
INTRODUCTION In 2004, international overnight arrivals were 19 million trips in Canada (CTC, 2005). Of these, U.S. overnight arrivals accounted for 15.1 millions (79.3%), whereas other overseas tourists were 3.9 millions (20.7%). Over the years, the U.S. market has consistently been the most important international tourism market for Canada. Traditionally, this market has been prompted by strong economic conditions enjoyed by Americans over the last few years (CTC, 2006). Nonetheless, significant barriers such as border hassles (passport requirements), exchange rate, and price of gas are expected to have a devastating impact on both travellers and destinations. In recent research (McWilliams, 2006), Canada’s position as a tourist destination for U.S. residents is receiving more competition from U.S. domestic markets and other destinations; especially Europe, Mexico, and the Caribbean. In addition, Canada’s satisfaction and value ratings have declined between 2000 and 2004. These may seriously impede potential growth. Therefore, there is no question it is critical to do continuous in-depth tourism marketing and tourist behaviour research on the U.S. markets. Tourist behaviour depends upon, interacts with, and occasionally determines other components of tourism, since there is a strong connection to marketing activities (Pearce, 2005). Typically, tourist behaviour research has attempted to explain the decision making processes of consumers facing several alternatives or choices (Dimanche & Havitz, 1994), and is also required to make appropriate marketing decisions (Moutinho, 1987). The literature on tourist behaviour is quite voluminous, but continues to grow as the dynamics and changes of tourists’ and hosts’ behaviour, and in the political, social and economic environment require further research. Basically, to understand tourist behaviour, the research begins with a consideration of the characteristics of the individual tourist him or herself, including their demographics, culture, social classes, personality, life-styles, motivations, perception, values, experience, beliefs, attitudes, etc., which are factors or motives influencing travel behaviour. Another consideration of tourist behaviour research is related to characteristics of the destination itself such as attractions/activities, setting, facilities, services, hosts, other tourists, management, etc., which are destination attributes and images. Finally, research needs to be implemented to understand and manage tourists’ on-site experience in terms of social, cultural, and environmental contacts while tourists are travelling. Through tourists’ whole experience, a variety of outcomes are produced in both tourists and a destination. The former includes tourists’ satisfaction, complaints, evaluation, and future behavioural intentions. The latter is composed of social, cultural, economic, and environmental tourism impacts, and management challenges (Kotler, Bowen, & Makens, 2003; Mayo & Jarvis, 1981; Moutinho, 1987; Pearce, 1982a, 1982b, 1988, 2005; Pizam & Mansfeld, 1999; Ryan, 2003; van Raaij, 1986). Specifically, this study investigated the U.S. overnight holiday-vacationers’ travel behaviour as the most significant international market for Canada. Thus, the purpose of the study is conceptually to propose a U.S. overnight holiday-vacationers’ travel behaviour model, empirically to test the study model proposed, and pragmatically to provide more clarity of understanding for the market.
THE PROPOSED MODEL The proposed conceptual model is presented in Figure 1. This study model was built based upon information in the International Travel Survey (ITS) and a review of the theories of travel behaviour and service quality. In brief, perception of travel services is influenced by the level of travellers’ activity participation, the amount of expenditures, and the number of destinations visited. Travel expenditure is itself produced by what types of activities travellers attended or participated in at the destination (travel activities) and how many different destinations were visited (destinations visited). Travel activity is influenced by the number and frequency of destinations visited. Figure 1. The Proposed Model
Travel Activity
+
+ + Destinations visited
Perception of Services
– (+)
+ Travel Expenditure
Antecedents of Perception of Travel Services In the proposed model, perception of travel services is posited as the ultimate dependent variable, which can be regarded here as perceived overall service quality in destinations; in other words, the travellers’ global judgment of or attitude towards the excellence and superiority of their travel experience, service and product (Parasuraman, Zeithmal, & Berry, 1988) or evaluative perception of travel services measured at a point in time (Cronin & Taylor, 1994). Therefore, perception of travel services is a cognitive evaluation, whereas satisfaction has been viewed as being an affective response to these cognitive evaluations (Otto & Ritchie, 1995). Based on these concepts, perceived travel services are influenced by the cognitive evaluation of individual components of the tourism experience, including where travellers go (destinations), what transportation they use, where they stay (accommodation), what they see and do (activities), and how much money they spend (expenditure). Accordingly, it is suggested that level of travel activity participation (+), amount of travel expenditure (- or +), and number of destinations visited (+) affect travellers’ perception of services. Antecedents of Travel Expenditure and Activity There has been a lack of empirically consistent research into the causal relationship between travel activity and expenditure. Therefore, this study attempts to investigate the influence on the U.S. overnight holiday-vacationers’ behaviour with respect to their travel spending in response to their level of activity participation. In general, involvement in some travel activities at destinations varies greatly in terms of seasonality, travellers’ preferences and income levels, market prices, and so on (Bryant, 1992). Interestingly, Jang’s (2002) research results show that two activity
factors (involving in local lifestyle and participating in cultural & social activities) out of eight were negatively related to travel expenditure. Therefore, each travel activity may positively or negatively affect travel expenditure depending on the characteristics of activities (or destinations) and the travelers themselves. In this study, however, the construct of travel activity was conceptualized as frequency levels of all activities participated in rather than investigated with each activity factor variable. The association of activities with expenditures was assumed in this model; that is to say, the more activities participated in, the higher the expenditure. Similarly, it was assumed that if travellers frequently visit diverse destinations during a period of time, they would spend more money. Therefore, it is suggested that travel expenditure is positively influenced by the level of travel activities participated in and the frequency with which destinations are visited. Travel activity is also positively influenced by the destinations visited. METHODOLOGY Data and Samples The ITS data was used for this study. It contains four main parts: Canadian resident trips abroad, Canadian resident trips to United States, overseas resident trips to Canada, and United States resident trips to Canada (Statistics Canada, 2004). Out of the four main categories, only the data set of U.S. resident trips to Canada in 2004 was used. Only the U.S. travellers’ main reasons for trip were considered for the purpose of sample selection. There are 13 detailed categories, including (1) meetings, (2) convention, trade show, and seminar, (3) other work, (4) holiday and vacation, (5) visit friends or relatives (VFR), (6) visit second home, cottage, and condo, (7) attend events and attractions, (8) personal (medical, wedding, etc.), (9) in transit to/from other countries, (10) educational study, (11) shopping, (12) other, and (13) commuting to work. Of these, the ‘holiday and vacation’ category under ‘pleasure travel’ was selected. A total of 41,639 samples of U.S. resident trips to Canada were collected in 2004 (Table 1). Of these, 10,097 were overnight pleasure travellers and 8,146 were overnight holiday and vacation trips; these were selected for analyzing the data and testing the proposed model. Table 1. Sampled U.S. Overnight Holiday Vacation Trips to Canada in 2004 Overnight Travellers
Total Number of Samples Total Overnight Travellers
Pleasure Travellers
Holiday Vacationers
18,894
10,097
8,146
41,639
Constructs and Measures Destinations visited In the ITS information, destinations visited in Canada include province, tourism region (TR), Census Metropolitan Area (CMA), Census Agglomeration (CA), and Census Division (CD). Travellers report a maximum of 15 places visited in Canada by their travelling party (Statistics Canada, 2004). Thus the information was originally collected in the form of open-ended answers. Then it was recoded by specific provincial, TA, CMA, CA, and CD code numbers. In this study, the score of destinations visited was calculated using the number of provinces visited by their travelling party divided by total number of reportable provinces (15) and then multiplied by 100.
Travel Activity Travellers report all activities in which they have taken part during the trip rather than during their visit. However, the ITS only consists of 19 specific activity variables, including (1) visiting friends or relatives, (2) attending a festival or fair, (3) attending a cultural performance (a play, a concert, etc), (4) visiting a museum or art gallery, (5) visiting a historic site, (6) visiting a zoo, aquarium or botanical garden, (7) attending a sports event, (8) shopping, (9) sightseeing, (10) going to a bar or night club, (11) going to a casino, (12) visiting a theme or amusement park, (13) visiting a national or provincial nature park, (14) participating in sports or outdoor activities, (15) boating (motor boat, sail boat, kayak, canoe or other), (16) golfing, (17) downhill skiing or snow boarding, (18) hunting, and (19) fishing. All activities were originally coded by using each activity’s number above. In this study, all activities were rescaled as binary measures: “0 (= no participation in each activity)” and “1 (= participation in each activity)”. Travel Expenditure Trip expenditures include all expenditures made by all members of the travelling party. Thus it is associated with the trip as a whole. The expenditures are broken down into the following five categories: (1) accommodation, (2) transportation in Canada, including gasoline expenditures, rented car, intercity plane, bus and train fares, boat tours, local bus, taxi, (3) food and beverage, (4) recreation and entertainment, and (5) other spending, including souvenirs, shopping, photos, etc. The expenditures indicate how much money was spent in each category rather than where money was spent on a specific trip (Statistics Canada, 2004). Expenditures were reported in Canadian dollars or converted to Canadian dollars. The travel expenditure scores were calculated by the ratio of each spending category to the total spending of a travel party. Perception of Travel Services Perception of services refers to the rating scores provided by travellers for five different aspects of their trip in Canada: (1) transportation, (2) accommodation, (3) hospitality of local people, (4) value for money, and (5) variety of things to do and to see (Statistics Canada, 2004). The variables were measured using a categorical rating scale (Zikmund, 2003), including “1 (= Good)”, “2 (= Average)”, and “3 (= Poor)”. In this study, ratings of perception of travel services were recalculated as travel service index (TSI) by rescaling “Good (= 100)”, “Average (= 50)” and “Poor (= 0)”. Data Analysis To achieve the purpose of the study, several methods of statistical analysis were employed including descriptive data analysis, factor analysis, and LISREL estimation. Simple statistics of variables and correlation matrix were produced by conducting the descriptive analysis. Exploratory factor analysis (EFA) was performed to identify dimensions of travel activities. In LISREL applications, confirmatory factor analysis (CFA) was implemented to validate the structure of factors in the model, and then structural equation modeling (SEM) was applied to estimate and identify causal relationships among the constructs in the proposed model. RESULTS Descriptive Statistics Rescaled or recalculated scores of the variables were used in this study to test the model rather than raw values of the data collected from the U.S. holiday-vacationers to Canada in 2004. The mean value of the destinations visited was 15.65 out of 100 (Table 2). The scores of “sightseeing”, “shopping”, and “visiting a historic site” were relatively higher than other activities, whereas “visiting a sports event” and “visiting a theme park or amusement park” were relatively lower. Among travel expenditure indices, values of “accommodation” and “food and beverage” were relatively higher than other spending categories. The values of four of the five travel services were viewed similar on the whole. However, the scores for “hospitality of local people” were highly perceived by U.S. overnight holiday-vacationers.
Table 2. Descriptive Statistics for the Study Variables Variables
n
Mean
Std.
Destinations Visited
8,146
15.65
13.93
Travel Activity TA2. Attend a festival or fair TA3. Attend a cultural performance (a play, a concert, etc.) TA4. Visit a museum or art gallery TA5. Visit a historic site TA6. Visit a zoo, aquarium or botanical garden TA7. Attend a sports event TA8. Go shopping TA9. Go sightseeing TA10. Go to a bar or night club TA11. Go to a casino TA12. Visit a theme or amusement park TA13. Visit a national or provincial nature park TA14. Participate in sports or outdoor activities TA15. Boating - motor boat, sail boat, kayak, canoe or other TA19. Fishing
8,146 8,146 8,146 8,146 8,146 8,146 8,146 8,146 8,146 8,146 8,146 8,146 8,146 8,146 8,146
0.47 0.58 1.77 2.35 0.92 0.16 3.63 3.75 1.22 0.43 0.23 1.97 1.94 0.56 0.68
1.51 1.65 2.49 2.62 2.00 0.91 2.44 2.38 2.22 1.45 1.08 2.55 2.54 1.62 1.77
Travel Expenditure SP1. Accommodation SP2. Transportation in Canada SP3. Food and Beverage SP4. Recreation and Entertainment SP5. Other (Souvenirs, shopping, photos, etc.)
8,139 8,139 8,139 8,139 8,139
30.90 8.69 18.84 9.06 8.90
25.87 13.75 16.85 14.55 13.84
Perception of Travel Services SV1. Transportation services SV2. Accommodation services SV3. Hospitality of local people SV4. Value for money SV5. Variety of things to see and do
5,842 7,517 7,858 7,823 7,544
16.14 16.10 17.59 15.89 16.71
5.62 5.38 4.64 6.05 5.08
Factor Analysis The construct of travel activity was measured using an EFA with a principal component method. In this study, four activity items (“visiting friends or relatives”, “golfing”, “down hill skiing or snow boarding”, and “hunting”) were eliminated because they were separately loaded when a preliminary EFA using all 19 items was performed. Also, some of them are specific seasonal activities. The EFA generated five dimensional factors that explained 52.67% of a total variance (Table 3). Appropriateness of factor analysis determined by examining the Kaiser’s measure of sampling adequacy was .76 (critical value of .60 according to Tabachnick & Fidel, 1989). All attributes had factor loadings of higher than .40 (Hattie, 1985). Five travel activity factors were labeled as “stereotypical travel activities”, “sports and outdoor activities”, “cultural activities”, “casino and nightlife activities”, and “events participation and theme park visitation”.
Table 3. Result of Factor Analysis for Travel Activities Factor and Variable
Factor Eigen- Variance Factor Communality Loading value Explained Mean
FTA1. Stereotypical Travel Activities TA5. Visit a historic site TA9. Go sightseeing TA13. Visit a national or provincial nature park TA4. Visit a museum or art gallery TA8. Go shopping TA6. Visit a zoo, aquarium or botanical garden
0.75 0.69 0.67 0.66 0.45 0.45
0.56 0.56 0.47 0.46 0.37 0.36
FTA2. Sports and Outdoor Activities TA14. Participate in sports or outdoor activities TA15. Boating - motor boat, sail boat, kayak, canoe or other TA19. Fishing
0.83 0.78 0.73
0.71 0.62 0.60
FTA3. Cultural Activities TA3. Attend a cultural performance (a play, a concert, etc.) TA2. Attend a festival or fair
0.76 0.74
0.61 0.56
FTA4. Casino and Nightlife Activities TA10. Go to a bar or night club TA11. Go to a casino
0.70 0.68
0.55 0.52
FTA5. Events Participation and Theme Park Visitation TA7. Attend a sports event TA12. Visit a theme or amusement park
0.71 0.66
0.56 0.48
2.86
19.08
2.40
1.66
11.05
1.06
1.23
8.21
0.53
1.10
7.33
0.99
1.05
7.00
0.20
Notes: 1) Principal component analysis was performed with Varimax rotation method using 15 travel activity index scale items. 2) Total variance explained: 52.67% 3) Overall MSA (Kaiser’s Measure of Sampling Adequacy): 0.77
Measurement Model Estimation To assess measurement validation in the model, the CFA with four constructs and sixteen factor variables were run using LISREL 8.52 (Jöreskog & Sörbom, 1993). The overall CFA resulted in a fit that was acceptable, with a χ2 of 1970.91 (d.f. = 99, p = .00), a goodness-of-fit index (GFI) of .97, a root-mean-square error of approximation (RMSEA) of .04, an adjusted goodness-of-fit index (AGFI) of .96, a non-normed fit index (NNFI) of .89, a comparative fit index (CFI) of .91. Results indicated that convergent validities of the factor-items to each construct in the model were demonstrated (Bagozzi & Yi, 1988). Structural Equation Modeling A structural model was constructed to further test the construct validity of the four construct variables representing the U.S. overnight holiday-vacationers’ travel behaviour in Canada. The structural model was estimated with four latent construct variables composed of one exogenous and three endogenous variables. To determine the causal relationship between exogenous and endogenous constructs, six direct path coefficients and three indirect paths were estimated. The model test was assessed through goodness-of-fit statistics and direct effects in the model were accomplished by examining the completely standardized parameter estimates and their tvalues (Jöreskog, 1993). As shown in Figure 2, fit indices provided by LISREL indicated that the model had acceptable (Hu & Bentler, 1995), representing absolute fit measures (χ2 of 1808.53, d.f.
= 99, p = .00, GFI = .97, RMR = 0.043, and RMSEA = 0.046), incremental fit measures (AGFI = 0.96 and NNFI = 0.90), and parsimonious fit measures (PNFI = 0.71, CFI = 0.92, IFI = 0.92, and RFI = 0.90). Consequently, the results of the structural equation modeling revealed that the model could be applicable and all four dimensions of travel behaviour had nomological validity. Figure 2. LISREL Estimate of the U.S. Overnight Holiday-vacationers’ Travel Behaviour Model -.47 ↓
0.94 ↓
0.97 ↓
0.99 ↓
0.99 ↓
Y1
Y2
Y3
Y4
Y5
1.21 -.25 0.16 0.09 0.07 Travel Activity 0.09 (6.75)
0.31 (35.65) 0.00→
X1
1.00
Destinations visited 0.01 (2.63)
Perception of Services
0.17 (13.47)
0.00 (0.42)
0.67 0.77 0.64 0.43 0.67
-0.21 (-3.55)
Y11
←0.55
Y12
←0.41
Y13
←0.58
Y14
←0.82
Y15
←0.55
Travel Expenditure 1.00 0.56 -7.27 0.50 0.81 Y6
↑ 1.03
Goodnessof-Fit Statistics
Y7
↑ 1.01
Absolute Fit Measures
Y8
↑ 2.35
Y9
↑ 1.01
Y10 ↑ 1.02
Incremental Fit Measures
Parsimonious Fit Measures
Chi-square
GFI
RMR RMSEA NULL Chi-square AGFI
NNFI
PNFI
CFI
IFI
RFI
χ299 = 1808.53 p = 0.00
0.97
0.043
0.90
0.71
0.92
0.92
0.90
0.046
χ2120 = 20334.83
0.96
Notes: 1) Numbers indicate parameter estimates, whereas numbers in parentheses indicate t-values. 2) Line arrows are significant paths, whereas a dashed arrow is not significant at p < .05. 3) Each observed variable indicates the following: X1=Number of destinations (provinces and tourism regions) visited in Canada, Y1=Stereotypical travel activities, Y2=Sports and outdoor activities, Y3=Cultural activities, Y4=Casino and nightlife activities, Y5=Events participation and theme park visitation, Y6=Spending on accommodation, Y7=Spending on Transportation in Canada, Y8=Spending on food and beverage, Y9=Spending on recreation and entertainment, Y10=Spending on other (souvenirs, shopping, photos, etc.), Y11=Transportation services, Y12=Accommodation services, Y13=Hospitality of local people, Y14=Value for money, Y15=Variety things to see and do.
DISCUSSION AND CONCLUSIONS The results provide strong support for the relationships between the constructs in the proposed model and help clarify the role of frequencies of destinations visited, level of travel activities, and amount of travel expenditure in the overall perception of travel services. In brief, travel activity and expenditure were positively influenced by destinations visited. The relationships between destinations visited and overall perception of travel services and between travel activity and overall perception of travel services were also positively related. The results show that the U.S. overnight holiday-vacationers’ frequencies of travel activity, amount of spending, and overall perception of travel services were more likely to relate to where they travelled, how many different
destinations they visited, and what activities they were involved in or participated in at particular destinations. Nevertheless, there was no significant relationship between travel activity and expenditure, and overall perception of travel services was negatively influenced by the U.S. overnight holiday-vacationers’ expenditure in Canada. One of the key findings in this study is that it provides a much needed empirical confirmation of the role of travel activity as a basic component of travel behaviour. In general, the more activities travelers engage in, the higher their overall expenditure in tourism. Nevertheless, the relationship between travel activity and expenditure was not significant in this study. Specifically, when the model was estimated, one construct of the travel activity as measured by five factor variables was used rather than five constructs of the travel activity. If the model were estimated by using five constructs of the travel activity, the result may be different. It is possible that each travel activity could have different effects (positive or negative) on travel expenditure, overall perception of travel services, and other behavioural components. From a theoretical perspective, the result implies that when tourism researchers investigate the effects of travel activity at a particular destination, they need to carefully consider which is the better way to measure the effect of travellers’ activities. It may depend on the research site (destination), purpose, and so on. From a pragmatic perspective, the result also implies that when tourism marketers want to promote travel activities or activity-based products as the destination’s economic benefits or identify them as travellers’ benefits, they need to carefully investigate which travel activity would potentially result in higher spending by travellers or a highly positive evaluation (perception), value for trip, satisfaction, and intention to revisit (loyalty). Another significant finding is that it also provides a much needed empirical confirmation of the role of travel expenditure as a basic component of travel behaviour. There has been much lack of empirical prior research on the causal relationships between travel expenditure and other travel behavioural components but there exists, of course, a number of studies related to travel expenditure (e.g., tourism economic impact studies or comparative descriptive analyses of it with other variables). In this study, the result indicates that travel expenditure has a significantly negative effect on overall perception of travel services, meaning that the U.S. overnight holidayvacationers to Canada negatively perceived overall service quality when they spent much money on their holiday trips. In other words, they can be regarded as a fairly price-sensitive market. Further empirical research should be undertaken to confirm this finding, since the positive or negative relationship may be vary by target markets. This is a potentially important result because the relationship may be more to do with the cost of products and services provided at a destination. In practice, tourism marketers who want to attract more U.S. holiday-vacationers should monitor their response and show greater flexibility in their price structure to reflect the demand and supply in the market. Also, tourism marketers should consider which strategy in terms of price, quality, and value is best applied to their destination. In addition, tourism marketers need to consider the current situation in Canada, that is to say the relatively poor exchange rate against the Canadian dollar, the high price of gas, and the new passport requirements faced by all U.S. travellers. In conclusion, this study makes several major contributions to the consumer behaviour and service quality literature in travel and tourism (destination studies), even though much further research should be undertaken to confirm and strengthen the theories and make use of the result in practice. First, it demonstrates the causal relationship among frequencies of destination visited, level of travel activities, amount of travel expenditure, and perception of travel services. There have been relatively few prior studies that have attempted to demonstrate this relationship. Second, although the ITS’s ultimate objective is to meet the balance of payments requirement of the Canadian System of National Accounts (Statistics Canada, 2004), the study identifies that the ITS data can be successfully used to provide fundamental information for tourism marketing strategies because it is a large scale, ongoing survey that is able to monitor markets over the years. Beyond the ITS information, future research should be more focused on diverse and in-
depth travel behaviour research of specific target markets in order to produce more useful pragmatic information and help tourism marketers/officials make decisions and implement marketing strategies effectively.
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Contact Information: Dongkoo Yun, Ph.D., Research Data Manager Tourism Research Centre School of Business Administration University of Prince Edward Island 550 University Avenue, Charlottetown, Prince Edward Island, Canada, C1A 4P3 Tel: (902) 566-6097, Fax: (902) 628-4302 E-mail address:
[email protected]
