The development of package tourism has been a significant feature in ..... Source: Australian Bureau of Statistics, December Quarter 1991 Overseas Arrivals.
Abstract This paper presents a choice model of package tours by Australian outbound travellers. The choice model is built using sociodemographics, travel characteristics, and psychographic attributes to predict the probability of choosing package tours using logit analysis. In contrast to earlier studies on packaged vacations, psychographic variables were included into the model to understand the travel mode choice by Australian travellers. The findings indicate that package purchasers are likely to be older, tend to travel with larger party size for touring/city/resort/cruise trip type, and seek a "being & seeing" benefit.
Sheauhsing Hsieh is a graduate student specialising in the areas of International Travel and Tourism in Forestry & Natural Resources Department, Purdue University, West Lafayette, Indiana. U.S.A. Joseph T. O'Leary is a Professor specialising in Recreation Participation and Behavior in the Forestry & Natural Resources Department, Purdue University. Alastair M. Morrison is an Associate Professor specialising in Tourism Marketing in the Restaurant, Hotel, Institutional, and Tourism Management Department, Purdue University. Pao-Hung, S., Chang is a former graduate student in the Restaurant, Hotel, Institute, and Tourism Management Department, Purdue University.
Modelling the Travel Mode Choice of Australian Outbound Travellers Sheauhsing Hsieh Joseph T. O'Leary Alastair M. Morrison and Pao-Hung S. Chang
(The data utilised in this paper were made available by Tourism Canada. The data for the Australia Pleasure Travel Market Study, 1988, was originally collected by Market Facts of Canada. Neither the collector of the original data nor Tourism Canada bear any responsibility for the analysis or interpretations presented here.)
Introduction The development of package tourism has been a significant feature in the post-war expansion of tourism (Pearce, 1988). The packaging of travel service is unique and different from the packaging of consumer products in a general store. A package tour is identified as a trip planned and paid for in a single price far in advance, covering both commercial transportation and accommodation (often meals and sightseeing are also included) (Morrison, 1989). Packages are popular with customers because they make travel easier and more convenient. At the same time, package tours help the industry to increase business in off-peak periods and attract specific or new target markets (Morrison, 1989). The package tour, therefore, provides many benefits to both travellers and tourism service groups and has become one of the greatest influences in the travel and tourism industry. THE JOURNAL OF TOURISM STUDIES Vol. 4, No. 1, MAY '93
Factors affecting the choice of package and non-package tours The vacation travel market has becom e highly competitive. Increases in discretionary time and money, as well as the variety of vacation packages, have given the potential traveller flexibility of choice. As a result, the factors influencing traveller decisions on the travel mode have become more complex. Se veral ma rketin g strategists have called attention to the importance of learning how travellers make decisions. That is, if the travel or tourism organisation wants to attract more travellers, it needs to understand who is making the decision and how that decision is made. Many factors affect the consumer decision process. The factors can
The consumer decision process is influenced by many factors . . . psychographic variables becoming more important to understand the behaviour.
come from marketing (e.g., product quality, price, distinctiven ess), social sources (e.g., family, reference group), indiv idual differences (e.g., sociodemographics, life style, personality), or psy chological process (e. g., motivation, perception) (Engel e t a l., 199 0; Sch iffm an & Kanuk, 1990). Since travel behaviour is a special form of consumption behaviour in terms of intangibles and consumption on-site (Morrison, 1989), the travel mode choice may be affected by additional factors such as travel characteristics, destination attributes, and past experience. Travel mode choice (package and non-package tour) research has often been examined (Askari, 1971; S heldon, 1986; Sheldon & Mak, 1987; Thompson & Pearce, 1980; U.S. Travel Data Center, 1985 ) in terms of the relationship between travel mode choice and consumer characteristics and trip attributes. Research found that travellers who were older, single women, with higher incomes 52
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tended to travel on package tours (Sheldon & Mak, 1987). Generally speaking, consumer characteristics such as age, living single, or a woman traveller and income are generally easy to identify and to measure; therefore, they can often be associated with use of specific products and with media (Schiffman & Kanuk, 1990). However, the travel and hospitality industry is different from the retail/sales industry. Travel characteristics such as trip type, destination, travel party size, travelling with children, or the length of trip, may affect the travel mode choice. Sheldon and Mak (1987) suggested that travellers tend to choose package tours when travelling to unfamiliar destinations, more than one destination, or spending a longer time on the trip. They further concluded that package tours are less attractive to larger party sizes and especially to parties travelling with children due to the economic considerations. In addition, purpose of trip may affect the travel m ode choice. Travellers visiting friends/relatives or participating in outdoor activities during th e trip may be less interested in choosing package tours because of the flexibility of a desired schedule an d activity components. The literature so far suggests that sociodemographics and travel characteristics are useful for the interpretation and understanding of travel mode choice. Nevertheless, the decision about travel mode for potential travellers may be more informative for tourism planners or marketers who have begun to focus on travellers' needs, attitudes, and motivation. Although sociodemographics and travel characteristics can a id in understa nding the potential market and how past travel characteristics affect future choice, marketers and planners still cannot fully understand why and how travellers make the travel mode choice (Goodrich, 1977; Mayo & Jarvis, 1983; Plog, 1987 & 1991). Therefore, psychographic variables having an impact on the travel mode choice are becoming more important to understand the choice
behaviour as well as marketing plans and promotion strategies. An early study conducted by Woodside and Pitts (1976) found that life-style information may be more important than demographic information in predicting foreign and domestic travel behaviour. Similarly, Abbey (1979) concluded that tour travellers prefer tours designed with vacation life-style information. Travel suppliers may create a package that is more compatible with the motivations, attitudes, and opinions of the tour traveller. Later, Schul and Crompton (1985) used two separate multiple reg ression procedures to examine the relative effects of the six psychographic variables and the sociodemographics on two measures of external search behaviour-travel planning time and the number of external travel orga nisations consulted by British travellers. They found that travel-specific psychographics would be more effective than sociodemographics for predicting externa l search behaviour. Thus, they suggested that using psychographic information for tour suppliers and marketers will become increasingly important in aiding the development of effective copy and promotional themes as well as in the selection of appropriate media for advertising. The model of travel choice behaviour From the previous review, sociodemographics, tra vel characteristics, and psychographic variables are recognised as important factors influencing travel mode choices. One of the ke y ingredients in tourism planning and decision-making is to develop travel choice models by analysing these travel factors. Models can be defined as "systems of hypotheses relating one or more dependent variables ... to several independent variables " (Mazance, 1989, p. 63). In studying travel and tourism, dependent variables could be the choice of a tourist destination, the likelihood of taking a future trip, the total visits, the length of stay, the travel
expenditure, or the travel mode choice. These independent variables (e.g., sociodemographics, travel characteristics, psychographics) then are u sed to exam ine the relationship with vacation choices, forecast tourism demand, or predict participation. Witt and Martin (1987) examined econ ometric models for forecasting international tourism demand. These models were developed for tourist visits from West Germany and United Kingdom to their respective tourist destinations (e.g., Austria, France, Greece, etc.) using sociodemographics, price, and trend variables. In addition, Silberman (1985) estimated the effects of demographic, economic, vacation, and destination characteristics on the length of stay of individuals on summer vacation trips to Virginia Beach, Virginia. Variables such as
Models built for one destination need to be augmented by travel mode choice models for quite different locations.
cost, distance, income, effect of the recession, more than one trip to Virginia Beach , etc. were significantly associated with length of stay using the Ordinary LeastSquare statistical method. From the aspect of travel mode choices, Sheldon and Mak (1987) presented a model that explained a traveller's choice of independent t r a v e l v i s - a - v i s travel on package tours by using logistic analysis. The significant contribution of this study is to suggest that the travel mode choice can be examined in a model based on the relationship between the travel mode choice and significant variables. However, this model was built on survey data for American travellers to the Hawaiian Islands and may not be applicable when examining other foreign package tour markets. Thus, it is of interest to examine and compare the travel mode choice model for other destinations. Additionally, most studies in travel behaviour use domestic and not THE JOURNAL OF TOURISM STUDIES Vol. 4, No. 1, MAY '93
international long-haul travellers. The factors affecting travel choice may be m ore complicated for international travel rather than domestic travel decisions. Therefore, understanding the choice of package and non-package travellers in terms of sociodemographics, travel characteristics, and psychographic attributes may help influence tourism development and plannin g as well as promotional a nd marketing strategies. The Australian travel market During the 1970s and 1980s, the num ber of ou tbound travellers from Australia has shown a definite upward trend. In 1970, only 352,500 Australian residents travelled overseas, compared to 1,286,900 in 1982 and 2,099,400 in 1991 (Bywater, 1989; Australian Bureau of Statistics, 1992). Traditionally, the major destinations of outbound Australians have been Europe and Oceania, with the top two country destinations being New Zealand and the United Kingdom. However, by 1983 Asia replaced Europe and Oceania as the major regional destination for outbou nd Australians, with Indonesia, Hong Kong, Singapore, Thailand, and Malaysia being the leading country destinations in Asia. In 1991, approximately 35% of Australian travellers went to Asia, with approximately 60% of these Asia-bound visitors going to the Southeast Asian nations. Also in 1991, the number of Australians visiting Southeast Asia (473,00) was more than those visiting Europe (4 37,200). The U.S.A. attracts a sign ificant share of Australian outbound travellers at an estima ted 308 ,800 in 19 91 (ABS, 1992) or just under 15% of all outbound Australians. The leading individual country destinations for Australians in 1991 were New Zealand (318,200), U.S.A. (308,800), U.K. (220,700), Indonesia (174,800 ), and Hon g Kong (130,500). The major purposes of trips among Australian outbound travellers in 1991 were holiday (54.8%), VFR (21.6%), business and attending 54
Table 1: Total Short-Term Departures of Australian Residents: 1970-91 (in thousands)a. 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981
352.5 413.9 504.5 638.1 769.7 911.8 973.8 971.3 1,062.2 1,175.8 1,203.6 1,217.3
1982 1983 1984 1985 1986 1987 1988 1989 1990 1991
1,268.9 1,253.0 1,418.5 1,512.0 1,539.6 1,622.3 1,697.6 1,989.8 2,169.9 2,099.4
a Short-term departures include those travellers whose intended or actual period of stay is less than 12 months. Source: Australian Bureau of Statistics.
conventions (18.8%), and other (4.7%) (ABS, 1992). The popularity of various overseas regions and countries varies according to trip purpose. With strong Australian ties to the U.K. and Europe, the U.K. and European co untries receive a much larger share of the VFR market than of the holiday and business/con vention market. Countries such Indonesia a nd Thailand, however, are primarily holiday destinations for Australian residents. With an estimated population of 17.34 million in mid-1991 (ABS, 1992), Australia represents a growth market in terms of both its international and domestic travellers. Domestic travel by Australians has enjoyed significant growth in recent
years, as has inbound travel by foreign visitors to Australia. In 1987, for the first time, the number of inboun d foreign visitors to Australia was greater than the number of outbound Australians. In 1989/90, Australians took 49,962,000 domestic trips within Australia; a trip being defined as any travel involving one or more nights stay (but less than 3 months) at least 40 kilometers from home (Bureau of Tourism Research, 1991). The 1989/90 trip figure was 10% higher than the comparable statistic for 1984/85. Some 77% of the approximately 50 million 1989/90 trips were intrastate and 23% were interstate. The trip purposes were pleasure/ holiday (41 .2%), VFR (27 .1%), business/conference/seminar (14.8%),
Table 2: Region of Intended Stay of Short-Term Australian Travellers (in thousands). Year Region 1990 1991 Oceania & Antarctica
Middle East & North Africa
Total 2,166.8 2,095.2 Source: Australian Bureau of Statistics, December Quarter 1991 Overseas Arrivals and Departures Australia, Catalogue No. 3402.
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private reasons (6.4%), and other (8.3%). The major recipients of these trips were New South Wales (32.1%), Queensland (22%), and Victoria (21.6%). Despite the increasing size of both the outbound and domestic Australian traveller markets, there is a need for more research data on this m arket beyond the broad travel volumes and demographic statistics. "T h e Changin g Australian T r a v e l l e r" study commissioned by the Australian F e d e r a t i o n o f Travel Agents (AFTA) in 1987 included an attitude survey of 500 potential and current Australian travellers. The study identified six "attitudinal" segments: Adventure travel (15%), first-time travel (20%), luxury m arket (10%), traditional tour market (15%), economy market (25%), and the special-purpose market (15%). In 19 90, the Commonwealth of Australia commissioned a research study to produce an attitudinal segmentation of the Australian domestic holiday market (BTR, 1991). Some 2,160 Australians were surveyed in the autumn of 1990 and factor/cluster analyses were used to define five attitudinal segments for the domestic travel ma rket: Conventional variety seekers (19%), dreamers (17%), grey experiencers (18%), try it oncers (27%), and secure doers (19%). A later study by Brain Sweeney and Associates for the Queensland Tourist & Travel Corporation involved a larger s a m p l e of 3,62 3 Au st ral ia ns w ho h a d taken a holiday during the past three years involving interstate, international, or extended intrastate travel. Conducted in the autumn of 1991, this study i de ntifi ed f o u r segm ents: The luxury seekers (24%), the u n i n v o l v e d b u d g e t conscious (24%), active families (34%), a n d stimulus s e e k e r s (18%). These segments were formed using cluster a nalysis on respondents' answers to a question on the im portance of various destination fea tu res and attractions as measured on a fivepoint Likert Scale. While som e o f these studies, including the Brian Sweeney &
Associates' work for Queensland contain data on preferences for packages versus independent travel arrangements, none have attempted a segmentation based thereon nor h ave th ey dev eloped predictive models based upon the data sets. The purpose of this study The purpose of this study is to understand the Australian travel market in terms of travel mode choice. More precisely, the objectives of this study are to (a) conduct a travel mode choice model of Australian travellers by analysing sociodemographics, travel characteristics, and psychographic attribu tes; (b ) identify th ose variables which distinguish the choice of package and non-package tours, and (c) provide r e c o m m e n dations to travel a nd tourism
incidence of qualified respondents was determined by recording the results of these screening procedures (Ma rket Facts of Canada Limited, 1988). The survey collected information on: (a) socioeconomic and demographic variables - age, gender, income, education, occupation, life cycle, and region; (b ) travel characteristics - party size, length of stay, trip type, travel season, and travel with whom; (c) travel philosophy, benefit sought, and product; (d) the most important information sources used to plan a trip; (e) the places visited on most recent and second most recent trips, etc. Selection of variables The dependent variable in this
Predictive models based on Australian data sets have not yet been developed.
organisations of host countries. Methodology Data Data from the Pleasu re Travel Markets Survey for Australia were collected from August 27 to September 18, 1988. A total of 1,503 personal, in-home interviews were conducted. All respondents were 18 years of age or older who took an overseas vacation in the past three years or intended to take such a trip in the next two years. The sample was drawn from five major cities: Sydney, Melbourne, Brisbane, Adelaide, and Perth. Households were screened b y interv iewers who followed predetermined walk patterns from a total of 300 computer-selected starting points. In households with more than one qualified respondents, a random selection was made using the next birthday m ethod. The
study is whether the respondent took a package tour while travelling overseas. In this study, there were 1,158 respondents who did take trips in the past three years, with 563 (48.6%) taking package tours and 5 95 (51.4%) who took non package trips in that period. The independent variables selected to predict and identify the travel mode choice between package and non-package travellers were: (a) sociodemograph ic factors: age, income, single woman traveller; (b) travel characteristics: length of trip, English-speaking destinations, travel party size, trip type, number of children on the trip, a nd (c) psychographic attributes (travel benefits sought). The travel benefit sought was identified based on the importance ratings for 30 items relating to reasons people might want to go on a vacation and experiences they might be looking for. Respondents were asked to respond using a 4-point Likert-type
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scale (1: strongly disa gree, 2: disagree, somewhat, 3: agree, somewh at, 4: strongly agree). Varimax rotated principal factoring with iterations was selected to explore possible dimen sions of the 30 travel benefits sought. A measure of the effectiveness of Factor analysis is factor loadin gs, which are standardised correlations between composite factors and origin al variables that are represented by the composites (Lewis, 1984). The heaviest loadings on each factor indicate which variables form the new composite. Each factor is given a label that corresponds to the item s it most nearly represents. Thus, six fa ctors which appear to underline the original set of 30 benefits sought
were identified as "being & seeing", "adventure getaway", "show & tell", "heritage", "physical activity", and "social escape" (Table 3). The 6 factors explained 49.2 % of total variance. Further, factor scores were used in subsequent analyses to represent the values of the factors. For each factor, the factor scores are obtained by multiplying the standardised values by the correspondin g factor score coefficients. The factor scores for each respondent were then incorporated into the model of travel mode choice.
reporting research results based on the analysis of data with a dichotomous dependent variable. The dependent variable in this regression equation is the logarithm of the odds that package tours were selected by Australian travellers. The odds are ratios of the number of package tours to the number of non-package tours. The dependent variable is then predicted by independent variables (socio-demographics, travel characteristics, psychographic attributes). This relationship can be expressed as follows: No. of package tours (sociodemographics 1n(______________________________________________) = f travel character, No. of non-package tours psychographics)
Logistic regression Logistic regression analysis used in this study is becoming an increasingly popular method of
The Logistic regression model is typically estimated by a method called "maximum likelihood
Table 3: Factors of travel benefits sought.
Travel benefit sought Cronbach's alpha Seeing & experiencing a foreign destination Experiencing new & different lifestyles Learning new things/increase knowledge Trying new foods Travelling to places historically important Seeing as much as possible Roughing it Experiencing simpler lifestyle Being daring & adventuresome Finding thrills/exciting Rediscovering myself Escaping from the ordinary
Being & Seeing 0.7040
Adventure Getaway 0.7362
Rotated Factor Pattern Factor 3 Factor 4 Heritage 0.6906
Physical Activity 0.6806
Social Escape 0.4662
0.6978 0.6967 0.6103 0.5808 0.5505 0.4775 0.6368 0.5899 0.5821 0.4869 0.4630 0.4488
Talking about trip after return home Going places friends haven't been Safe/secure travel Having fun/being entertained Feeling at home away from home Indulging in luxury Meeting people with similar interests Visit friends/relatives Visit places family came from Family is together Reliving past good times Sports participation Sports spectating Physical activity Get away from demands of home Change from busy job Doing nothing at all
Tell & Show 0.6922
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0.6173 0.5658 0.5646 0.5408 0.5184 0.5027 0.4085 0.7779 0.7558 0.6365 0.4811 0.7664 0.7576 0.6053 0.6991 0.6183 0.4664
estimation (M LE)" (Aldrich & Nelson, 1984). To test if the odds ratio is significantly different from 1.0 (no association) requires use of the Chi-square statistic. The Chisquare statistic is referred to as the likelihood-ratio Chi-square or the likelihood ratio statistic. This likelihood ratio is used to test that the model being estimated is correct versus the unrestricted alternatives. "-2" times the logarithm of the likelihood-ratio statistic distributed as a Chisquare distribution is used to present the goodness of fit. A large Chi-square value suggests that the model of independence is an inappropriate description of the observed data. On the other hand, a small Chi-square value indicates that the model of independence provides a reasonable description of the data (Morgan & Teachman, 1988). Thus, the goal was to find a model that fits the data well enough such that the Chi-square value is small. In addition, since there is no R 2 statistic in logit models with a comparable interpretation, the "pseudo R 2 " proposed by Aldrich and Nelson (1984, p. 57) is used to measure the quality of the fit improvement. The formula for computing pseudo-R 2 is: Pseudo R 2 = C/(N+C), where C is the Chi-square statistic for overall fit, and N is the total sample size. The selection of variables to be included in a regression model is important. Schroeder (1983) suggested two general techniques which can be applied: (a) preselection of variables based upon theory developed by previous research, where the researcher has sound theoretical reasons for including variables, and (b) the use of stepwise regression to determine the significant variables, where little is known about the significance of the variables in question. In order to interpret independent variables accurately and find an essential model with significant variables, a Stepwise Logistic regression procedure was applied in this study. From the Logistic regression analysis, the reported coefficient estimates measure the relationship
between the independent and dependent variables. Estimated standard errors provide a useful measure of the likely variation in the estimated coefficients. The tstatistic is used for testing the null hypothesis that a coefficient is 0. Empirical model The empirical m odel for the Australian's choosing package tours can be expressed as follows: 1n[
] = Σbjxji 1
Where Pi: the probability that an individua l (i) will take a package tour X1i: age X2i: income X3i: single woman, 1: if a single female traveller; 0: if not a single female traveller X4i: length of trip (nights) X5i: E n g l i s h - s p e a k i n g destination(s), 1: i f it is an English-speaking destination, 0: if it is not an Englishspeaking destination X6i: travel party size X7i: number of children travelling with X8i: purpose of the trip, 1: if it is a touring, resort, city, cruise, or other purpose trip; 0: if it is a VFR or an outdoor purpose trip X9i: being & seeing, 1: if seeking the "being & seeing" benefit, 0: if not seeking the "being & seeing" benefit X10i:adventure getaway, 1: if seeking the "adventure getaway" benefit, 0: if not seeking the "adventure getaway" benefit X11i:show & tell, 1: if seeking the "show & tell" benefit, 0: if not seeking the "show & tell" benefit X12i:heritage,
1: if seeking the "heritage" benefit, 0: if not seeking the "heritage" benefit X13i:physical activity, 1: if seeking the "physical activity" benefit, 0: if not seeking the "physical activity" benefit X14i:social escape, 1: if seeking th e "social escape" benefit, 0: if not seeking the "social escape" benefit The study expects b1>0, b2>0, b3>0, b4>0, b5>0, b60, b 1 0 0 , b120, b14