Exploring the Relationship between Traveler Types and Travel Route Types

Transcription

1 International Journal of Basic & Applied Sciences IJBAS-IJENS Vol:14 No:02 48 Exploring the Relationship between Traveler Types and Travel Route Types Gao, Jing-Hui 1 Hsueh, Ya-Hui 1* 1 Department of Regional and Social Development, National Taichung University of Education, Taiwan * Corresponding author doseo.doseo@gmail.com Abstract-- This research focused on the arrangement types of travel nodes, according to 350 valid questionnaires of conducting in-depth interviewing and questionnaires survey of travelers stayed at Dong-Gang area, and examined the relationship between the traveler types and the travel route types by using cross tabulation analysis. According to the extent of mindful plan before itinerary and the average staying time of a tourist spot, the travelers may be reduced to three types-main attraction visitors, specialists, and explorers. The assessment of the different properties of the three travel routes (P1, P2, P3) has some practical implications. It is recognized that P1 travel routes and P2 travel routes are more demonstrated by the travelers, while P3 travel routes are less in proportion. A cross tabulation analysis was conducted between the traveler types and the travel route types. The chi-square test was adopted to verify whether there is any relevance between traveler types and travel route types. The statistical significance (p <.001) shows a significant difference between the two variables. Meanwhile, the prediction between traveler type and travel route type based on is the more mindful planned travelers staying for over two days with radiating hub types and the random traveler staying for less than two days with random exploratory types. Index Term- traveler type, travel route type, cross tabulation analysis, Ⅰ. INTRODUCTION Classification for traveler types Zillinger (2007) investigated travel routes by the theoretical perspective of time geography analysis, indicated that an individual travel rhythm, which can be defined as a travel route, influenced by the availability of time, independent from the travelers sites that are visited. Zillinger also highlights the key factor in determining travel routes is the amenities of tourist attractions, which is clear that the existence of tourist attractions are fundamental to a journey. While a number of studies have been conducted mapping and modelling inter-destination movements in various locations (Mings & McHugh, 1992; Lue et al., 1993; Oppermann, 1995; Stewart & Vogt, 1997; Flognfeldt, 1999; Lew & McKercher, 2002), Mckercher & Lau (2008) categorized the movement patterns of travelers based on the number of stops within a destination, proposed that time availability influence deeply on tourists exploring destinations as well as both the number of tourist attractions visited and intensity of visitation. Mckercher & Lau (2008) also explored the relationship between travel route types with, noted that in variations were not significantly associated with travel route types. Both of the travelers, displayed an unspecified local travel types or complex travel types, had the short staying duration. In addition, Beeco et al. (2012) used GPS data tracing

2 International Journal of Basic & Applied Sciences IJBAS-IJENS Vol:14 No:02 49 travelers activity space to identify actual travel pattern differences between wanderers and planners. The participants were then separated out by Beeco et al. into four groups: low planning and low wandering (Ambivalent Travelers), low planning and high wandering (Traditional Wanderers), high planning and low wandering (Traditional Planners), and high planning and high wandering (Planned Wanderers). Zakrisson & Zillinger (2012) also used GPS to trace the movement patterns for the travelers, separated out the travelers into three groups:main attraction visitors (with highly ability of movemet to primary destinations, visiting the highlight spots with accessibilty of traveling facilities for tourism promoting), specialists ( focusing on small region with special or thematic spots, for example visiting music festival or village center as primary destinations), wanderers (creating a high wandering score, enjoying not only on highlight sopts but also on others with tourist attractions). In conclusion, numerous studies have identified traveler types that suggested differences in travel exploration and understanding, and identified explorers with highly movement for visiting not well-known spots while specialists with understanding demonstrated on low movement for special or thematic spots, main attraction visitors moving to larger region than specialists focusing on thoses spots of promoted by government for exploration and understanding. In this Dong-Gang area research according to questionnaire survey, we proposed on alternative traveler type-explorers, rather than wanderers who are mainly self-centered, those who conduct in-depth exploration of the attractions that they are interested in. Therefore, in this research the travelers were divided into three types-main attraction visitors, specialists and explorers. Classification for travel route types Many researchers indicated that the effort for exploring travel route types is conducive to tourism planning for example analyzing spatial structure of travelers' routes for travelers' needs, provideing diverse perspectives to predict travelers routes and enhance the appeal of tourist attractions (Oppermann, 1995; Pearce, 1990; Hwang & Fesenmaier, 2003). Travel route types can be divided into different categories based on different indicators provided by the researcher. Pearce (1995) divided tourist routes into four categories: tourist route mode, origin-destination mode, structural mode and evolution mode. Flognfeldt (1999) proposed four patterns of tourist routes: Day trips, Resort trips, Base holiday trips and Round trips. Based on the study in Branson, U.S.A., Stewart & Vogt (1997) sorted out problems concerning travel routes that had not been solved by LCF (1933); that is the difference between regional travel route patterns and trip chained patterns. Travel nodes can be defined as the meaning of the origin and the destinations in the itinerary from traveler s accommodation to tourist spots as a analysis concept for travel route type. Based on this conception of travel node, travel route is with variations according to the different arrangements among travel nodes for different itineraries of travelers. Travel route types identified by previous researchers were by different indexes with great diversity (Table I) (Flognfeldt 1992; Lue 1993; Oppermann et al 1995; Stewart & Vogt 1997; Lew & McKercher 2006). Lew & McKercher(2006)proposed three travel route types: P1 type, P2 type, P3 type for exploring traveler s routes based on the point of accommodation in a local destination zone. P1 type means that starting journey and return trip all trace the same route back to the place of accommodation, and P2 type indicates starting journey and return trip trace different route to the place of accommodation, while P3 type is a type combined with P1 type and P2 type. Generally, the more transport accessibility and increase of time budgets, the more all-centric behavior and destination knowledge will result in travel route types more reflective of P2 tpye and P3 type (TableⅡ).

3 International Journal of Basic & Applied Sciences IJBAS-IJENS Vol:14 No:02 50 The reason why this research do not used other analysis concept of travel route types, proposed by such as Flognfeldt (1992), Lue (1993), Oppermann (1995) and Stewart & Vogt (1997), is that their conceptions are not able to be demonstrated in diversity properly due to focusing on points of origins of homes, since all travelers is supposed to start from their homes and finally return back home after visiting all tourist spots, and finally all the travel route types will be defined to P2 circular types. This research using the viewpoint proposed by Lew & McKercher (2006) to explore the arrangements of travel nodes aims to demonstrate the diversity of travel route types in the Dong-Gang area. In other words, Lew and McKercher refer local destination zone to a kind of consuming area with a lot of places for leisure and activity, so Orlando may be a local destination, and Disney never is a local destination instead of being a resort complex. The conception of travel route types based on accommodation locations, proposed by Lew & McKercher (2006), can be applied to this research because all the samples were from Taiwan main island, and they travelled for more than two days to spend several nights in the Dong-Gang area for travelling; in contrast to the conception, proposed such as by Flognfeldt (1992), Lue (1993), Oppermann (1995) and Stewart & Vogt (1997) to analyze travel route types from original places of homes, not to clarify the diversity of travel routes types in the Dong-Gang area properly, since all tourists may set out from their homes and finally return back home after visiting all tourist spots, and finally all types will be defined to circle route types making this research to be less meaningful. In contrast to the above scholars travel route types that set the residence (home) as the starting point, Lew & McKercher (2006) proposed travel route types that set the accommodation as the starting point, and divided it into three types of P1, P2 and P3. McKercher & Lau (2008) proposed another way of categorizing travel route types, and grouped 78 different types of tourist paths into 11 route types, but the classification was too complicated, which could not be well applied to the simple paths in our this study. Hence, the classification method of Lew & McKercher (2006) was adopted in this study. Table I Classifications for travel route types Year Travel Path Patterns Mings Mchugh Direct route, Partial orbit, Full orbit, (1992) Fly/Drive Lue Crompton single destination, en route, base camp, & Fesenmaier regional tour, trip chained (1993) Pearce(1995) tourist route mode, origin-destination mode, structural mode,evolution mode Oppermann Single destination, Base camp, Stop-over (1995) pattern, Full loop, Destination area loop, Open jaw loop, Multiple destination areas loop Stewart &Vogt (1997) Flognfeldt Day trips,resort trips,base holiday (1999) trips,round trip Lew & Point-to-Point Patterns (P1) McKercher Circular Patterns (P2) (2006) Complex Patterns (P3)

4 International Journal of Basic & Applied Sciences IJBAS-IJENS Vol:14 No:02 51 Table Ⅱ The classication of travel route types by Lew & McKercher (2006) Broad Type Sub-broad Type P1-Point-to-Point P1a-Single Point-to Point, Patterns P1b-Repetitive Point-to Point P1c-Touring Point-to Point P2-Circular Patterns P2a-Circular Loop, P2b-Stem and Petal P3-Complex P3a-Random Exploratory, Patterns P3b-Radiating Hub Ⅱ. MATERALS AND METHODS The tourist spots in the Dong-Gang area include Pen Bay National Leisure Zone and Liu Qiu Island. Hot tourist spots in the Dong-Gang area include natural tourist resources and cultural tourist resources, the former including Marine Leisure District and Qing-Zhou Recreation District, while the latter including the Overseas Chinese Fish Market, Haizhiqiu, sea food Street, Dong-Long temple, Zhen-Hai temple and Circum-baycycling track. Visitors can take the yacht around the Pen Bay to enjoy the mangrove and go to the Oyster Shell Island to learn about oyster cultivation, which will become the world-class water sports & resort base in the future. Liu Qiu Island is the only coral island in the outlying islands of Taiwan. The island is rich in landscape resources, bizarre rocks and stones, intertidal zones with rich ecological significance, brilliant Ryukyu sunset glow, bright stars and fireflies at night, and a variety of water activities and snorkeling. In this research, in-depth interviews were conducted to explore the characteristics of traverlers' activities and identify the travelers to different types. Restricted by respondents willingness to be interviewed, convenience sampling rather than random sampling was adopted. However, disputes may arise from the convenience sampling--the representativeness of samples. As a result, in order to increase the availability of the samples, results obtained via the questionnaire survey from February 2012 to August 2013 are designed to indicate the travelers feelings towards their travel in the Dong-Gang area during this period rather than the average travel conditions of each month or the whole year. In-depth interviews and questionnaire surveys were distributed in those tourist sopts frequently visited by the travelers in the Dong-Gang area such as the Overseas Chinese Fish Market, Lamay Island, Dong-Long Temple and Marine Leisure District. The 350 valid questionnaires, containing three parts-traveler s properties, characteristics of travelers activities and drawing attractiveness, have been revised according to experts advice. This research used descriptive statistical method, tested by chi-square to analyze different travelers types, and was taken as the independent variable, while travel route type as the dependent variable, both of which were subjected to the correlation analysis. Variables originally class variables were turned to nominal variables for the chi-square test analysis. The statistical test by means of cross tabulation analysis was to verify whether significant difference variables exist in various dimensions, travel route types, attributes of tourist spots and the frequency distribution of variables. Chi-square test was used to examine the differences of traveler types for more than 80% of the expected frequency of each cell in the chi-square test should be bigger than 5, or obvious deviation will show in the results. When the number of cells is too small, there are solutions available such as cell mergence, increase of samples, and elimination of samples and correction of formula. Therefore, in order to improve the accuracy of the chi-square test, in case of insufficient frequencies of some options, this research merges similar options, and deletes those options with insufficient frequencies and little value that can not be merged.

5 International Journal of Basic & Applied Sciences IJBAS-IJENS Vol:14 No:02 52 Ⅲ. RESULTS AND DISSCUSION The relationship between traveler types and travel route types According to the extent of mindful plan before itinerary and average staying time at a tourist spot, the travelers reduced to three types-main attraction visitors, specialists, and explorers, among which main attraction visitors account for the largest proportion of 67% and specialists account for 18%, while explorers for 15% respectively based on questionnaire survey (Table Ⅲ). The association of traveler types and travel route types was the main attraction visitors preferred to adopt stem and petal pattern (24%), point-to-point (20%) in order to visit planned attractions easily and make spatial movement effectively; the specialists adopt single point-to-point pattern (8%) in order to visit planned attractions easily and make spatial movement effectively (Table Ⅳ). Based on Table Ⅳ, it is recognized that P1 travel route type (single point to point, touring point to point) and P2 travel route type (circular loop, stem and petal ) are more demonstrated by the travelers, accounting for 50% and 44%; While P3 travel route type (radiating hub) is less in the proportion only accounting for 6%. If comparing on sub-type travel route, stem and petal type (P2b) is more demonstrated by the travelers (30%), and then are touringpoint to point(p1b), single point to point (P1a) (26%,24%),circular loop (P2a) for 14%,radiation hub (P3b) for 6%; While repetitive point to point (P1c) and random exploratory (P3a) are no traveler demonstrated on. Table Ⅲ Three traveler types in the Dong Gang area Traveler Types Samples (N=340) Percentage (%) Main attraction visitors % Specialists 61 18% Explorers 53 15% Total % Source: Questionnaire survey Table Ⅳ Comparison of travel route types on the travelers in the Dong-Gang area Travel Route Types Samples Percentage Sub-Total Sub-Total (N=340) (%) Samples Percentage P1 Single Point to Point(P1a) Touring Point to Point(P1b) % 26% % Circular Loop(P2a) 47 14% P % Stem and Petal(P2b) % P3 Radiation Hub(P3b) 20 6% 20 6% Source: Questionnaire survey

6 International Journal of Basic & Applied Sciences IJBAS-IJENS Vol:14 No:02 53 The chi-square test is adopted to verify whether there is any relevance between traveler types and travel route types in this research (chi-square vertical bar as Figure 1). The statistical significance shows traveler types associated with travel route types (X 2 =17.766, p <0.001). TableⅤshows that the cross-tabulation analysis of traveler types and travel route types, in which main attraction visitors frequently adopting stem and petal patterns (24%) and point-to-point patterns (20%) indicats that in order to visit preferred attractions they make effective time and spatial movement as they can; specialists frequently adopting single point-to-point patterns (8%) indicats that they would concentrate in relatively narrow regions, prefer to explore special or thematic attractions, e.g. to pay respects in the Dong-Long temple, buy fish in the Overseas Chinese Market or probably join in an event in the Marine Leisure District; while compared with the other two types, explorers frequently adopting single point-to-point patterns (6%) but also radiation hub patterns (2%) accounting for a relatively large proportion. Explorers demonstrated travel type of radiation hub pattern with high degree of mobility to visit the less known, nearby and densely distributed attractions. Table Ⅴ also shows that single point-to-point, touring point-to-point, circlar loop, stem and petal are mainly adopted by main attraction visitors (respectively 10%, 20%, 10%, 24%), while specialists, explorers are mainly adopted single point-to-point (respectively 8% and 6%). It is observed that the travelers of specialists and explorers adopting single point-to-point patterns intend to stay as long as possible for exploring preferred spots. The reason why the travelers in this study area didn t frequently adopt radiation hub type need to be futher explored. Table Ⅴ Cross tabulation analysis for the traveler types and travel route types Traveler types Single Touring Circular Stem and Radiation Sub-Total point to point point to point loop petal hub Main attraction visitors 35(10%) 68(20%) 32(10%) 82(24%) 9(3%) 226(67%) Specialists 26(8%) 12(4%) 8(2%) 11(3%) 4(1%) 61(18%) Explorers 21(6%) 8(2%) 7(2%) 10(3%) 7(2%) 53(15%) Total 82(24%) 88(26%) 47(14%) 103(30%) 20(6%) 340(100%) χ2 = , df =8, p < n = number of travel route types per traveler type.

7 International Journal of Basic & Applied Sciences IJBAS-IJENS Vol:14 No:02 54 Fig. 1. Traveler types and travel route types in the Dong-Gang area for cross tabulation The prediction between traveler type and travel route type based on This research used, traveler type, and travel route type variables for cross tabulation to study the degree of relationship on the spatial behaviour of travelers and the interaction of these variables. The of travelers between a traveler type travel route type pair was used as a dependent variable. Table Ⅵ and Table Ⅶ show the results of chi-square test, indicating that over two days is more representative of explanatory variable in the crosstabulation analyses because there are confirmed significant relationships between traveler type and travel route type (level of significance values are p>0.001 and p<0.001). The values of Pearson coefficient and Tau asymmetric correlation for of over two days are both greater than of one day ( > 5.459, > ), indicating that the variable prediction of for two days is stronger than that of for one day. Both values of level of significance of Pearson coefficient and Tau asymmetric correlation for the of over two days variable appear strongly significant at level, providing more confidence for this explanation. Although the value of contingency coefficient for one day is greater than that of over two days (0.329 > 0.165), the level of significance is not significant (p = > 0.001), indicating that one day does not seem as a significant variable as there is no correlation in the differences between traveler types and travel route types.

8 International Journal of Basic & Applied Sciences IJBAS-IJENS Vol:14 No:02 55 Table Ⅵ Cross tabulation analysis for travel route types, traveler types and Staying Traveler Types Main Attraction Specialists Explorers Total Duration Travel Route Types Visitors One P1 travel route type 53 (16%) 35 (10%) 19 (6%) 107 (32%) Day P2 travel route type 54 (16%) 16 (5%) 13 (4%) 83 (25%) P3 travel route type 2 (0%) 1 (0%) 1 (0%) 4 (0%) Sub-Total 109 (32%) 52 (15%) 33 (10%) 194 (57%) Over P1 travel route type 50 (14%) 3 (1%) 10 (3%) 63 (18%) Two P2 travel route type 60 (18%) 3 (1%) 4 (1%) 67 (20%) Days P3 travel route type 7 (2%) 3 (1%) 6 (2%) 16 (5%) Sub-Total 117 (34%) 9 (3%) 20 (6%) 146 (43%) Total 226 (66%) 61 (18%) 53 (16%) 340 (100%) χ2 = , df =8, p < n = number of travel route types per traveler type. Table Ⅶ analysis for travel route types, traveler types and Analysis Pearson Pearson Tau Asymmetric Tau Asymmetric Contingency Coefficient Contingency Coefficient p < Independent Variable Test Value F Value Level of Significance One day Over two days One day Over two days One day Over two days Ⅵ. CONCLUSIONS In conclusion, this research not only confirmed the complex nature of travel route types, but also identified related factors that influenced travel route types. The of the travelers of the independent variable was categorized into two dichotomous groups, i.e. over two days, one day; while the travel route type and traveler type of the travelers the dependent variable was

9 International Journal of Basic & Applied Sciences IJBAS-IJENS Vol:14 No:02 56 categorized into three and four dichotomous groups, i.e. main attraction visitors, specialists, explorers and P1 type, P2 type, P3 type. To estimate these, three correlation analysis were conducted leading to Pearson correlation coefficients, Tau asymmetric correlation coefficients and Contingency coefficients, respectively. This research provides empirical evidence that traveler type-travel route type related variables are related to of travelers within the Dong-Gang area. The more lengh of is, the more likely the traveler type and travel route type seem to be represented as main attraction visitor and P1 type REFERENCES [1] Beeco, J.A., Huang, W.J., Hallo, J. C., Norman, W.C., McGehee, N.G., McGee, J. & Geotcheus, C. (2012). GPS tracking of travel routes of wanders and planners. Tourism Geographies 15(3):1-23. [2] Fesenmaier, D. R. & Lieber, S. R. (1985). Spatial structure and behavior response in ourdoor recreation participation. Geografiska Annaler 67B: [3] Flognfeldt, T. (1999). Traveler geographic origin and market segmentation:the multi trips destination case. Journal of Travel & Tourism Marketing 8(1): [4] Hanson, S. (1980). Spatial diversification and multipurpose travel:implication for choice theory. Geoqraphical Analysis 12: [5] Hwang, Y. H. & Fesenmaier, D. R. (2003). Multidestination pleasure travel patterns: Empirical evidence from the american travel survey. distribution of tourists. Annals of Tourism Research 33(2): [9] Lue, C. C., Crompton, J. L. & Fesenmaier, D. R. (1993). Conceptualization of multi-destination pleasure trips. Annals of Tourism Research 20: [10] McKercher, B.& Lau, G. (2008). Movement patterns of tourists within a destination. Tourism Geographies 10(3): [11] McKercher, B., Shoval, N., Ng, E, & Birenboim, A. (2012). First and repeat visitor behaviour: GPS tracking and GIS analysis in Hong Kong. Tourism Geographies 14(1): [12] Mings, R. C.& K. E. Mchugh (1992).The spatial configuration of travel to yellowstone national park. Journal of Business Research 30: [13] Oppermann, M. (1995). A model of travel itineraries. Journal of Travel Research 33: [14] Pearce, D. G. (1990).Tourism the regions and restructuring in new zealand. Journal of Tourism Studies 1(2): [15] Stewart, S. I. & C. A. Vogt (1997). Multi-destination trip patterns. Annals of Tourism Research 24(2): [16] Wall, G. (1978). Competition and complementarity: A study in park visitation. International Journal of Environmental Srudies 13: [17] Wall, G. (1997). Tourism attractions:points,lines,and areas. Annals of Tourism Research 24(1): [18] Zakrisson, I. & M. Zillinger (2012). Emotions in motion: tourist experiences in time and space. Current Issues in Tourism 15(6): [19] Zillinger, M. (2007). Tourist routes: A time-geographical approach on German car-tourists in Sweden. Tourism Geographies 9(1): Journal of Travel Research 42: [6] Lew, A. & McKercher, B. (2006a). Modeling tourist movements a local destination analysis. Annals of Tourism Research 33: [7] Lew, A. A. & McKercher, B. (2002). Trip destinations, gateways and itineraries: The example of hong kong Tourism Management 23(6): [8] Lew, A. A. & McKercher, B. (2006b). Tourist flows and the spatial