A case study of Hong Kong residents’ outbound leisure travel

A case study of Hong Kong residents’ outbound leisure travel

ARTICLE IN PRESS Tourism Management 25 (2004) 267–273 Case study A case study of Hong Kong residents’ outbound leisure travel Hanqin Q. Zhanga,*, H...

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ARTICLE IN PRESS

Tourism Management 25 (2004) 267–273

Case study

A case study of Hong Kong residents’ outbound leisure travel Hanqin Q. Zhanga,*, Hailin Qub, Venus Mo Yin Tanga a

School of Hotel and Tourism Management, The Hong Kong polytechnic University, Hom Hung, Kowloon, Hong Kong b School of Hotel and Restaurant Administration, Oklahoma State University, Stillwater, OK 74078, Hong Kong Received 21 March 2002; accepted 31 March 2003

Abstract Hong Kong is one of the largest outbound tourist generators in the Asia-Pacific region and the outbound travel has grown from 1.8 million in 1989 to 4.8 million in 2001. The purpose of this study was to investigate Hong Kong residents’ preferences toward destination choice of outbound leisure travel. In-depth personal interviews were conducted with 292 Hong Kong residents. A factor analysis was used to identify the dimensions of destination selection attributes and the one way analysis of variance with Duncan’s multiple range test was run to test the difference among specific groups of travelers. It was found that the dimension of safety is the top concern for Hong Kong residents when they choose travel destinations. Respondents with different demographic backgrounds were found to have different destination attribute preferences. r 2003 Elsevier Ltd. All rights reserved. Keywords: Hong Kong; Destination preferences; Outbound travel

1. Introduction Tourism has been one of the most significant and consistent growth industries in the world. Hong Kong is the fourth largest tourist generating market in the Asia Pacific region, after Japan, Taiwan and Australia. With the relatively high living standard and disposable income, overseas travel has become a way of life for many Hong Kong residents. Although Hong Kong’s economy has been less booming in recent years, this had little impact on the outbound leisure travel of Hong Kong residents. The number of outbound travelers increased from 3.8 million in 1997 to 4.8 million in 2001 (excluding those who traveled to the Mainland China and Macau). Over 4.8 million Hong Kong residents traveled abroad in 2001, representing more than 70% of Hong Kong’s population (see Table 1). The steady growing outbound travel market in Hong Kong has drawn tremendous attention from local and international tour companies to understand the destination preferences of Hong Kong residents’ outbound travel.

*Corresponding author. Tel.: +852+2766-6368; fax: +852+23629362. E-mail addresses: [email protected] (H.Q. Zhang), [email protected] (H. Qu). 0261-5177/03/$ - see front matter r 2003 Elsevier Ltd. All rights reserved. doi:10.1016/S0261-5177(03)00096-7

Traditionally, traveling to Mainland China and Macau has not been considered outbound travel and it is only regarded as quasi-domestic travel. Moreover, Hong Kong became a part of China after July, 1997 and so did Macau after December 1999. Therefore, Hong Kong residents traveling to Mainland China and Macau were excluded in this study. Understanding travelers’ preferences and travelrelated behavior is vital for tourism marketers in determining market segments and in designing advertising campaigns. The purpose of this study is to understand the Hong Kong outbound travelers’ preferences. The objectives of the study were: (1) to identify the travel related characteristics of Hong Kong residents; (2) to assess Hong Kong residents’ preferences of the destination attributes that affect their leisure travel destination choices; (3) to investigate the relationship between the demographic characteristics of Hong Kong residents and their preferences for leisure travel destination choice.

2. Literature review Consumer preferences for different travel destinations form a conceptual framework which deals with several

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Table 1 Hong Kong resident outbound departures 1997–2001 Destination The Americas Europe and the Middle East Australia and N.Z. North Asia South and Southeast Asia Taiwan All Othersa Grand Totalb

1997

Growth (%)

1998

Growth (%)

1999

Growth (%)

2000

Growth (%)

2001

Growth (%)

446,109 342,012

3.1 8.1

432,233 332,633

3.1 2.7

398,255 323,873

7.9 2.6

399,206 347,556

0.2 7.3

376,635 347,612

5.7 o0.1

226,693 623,283 1,711,044

2.7 30.9 9.2

236,636 879,607 1,888,443

4.4 41.1 10.4

230,350 778,186 1,985,675

2.7 11.5 5.1

231,576 738,991 2,389,619

0.5 5.0 20.3

237,493 761,616 2,504,621

2.6 3.1 4.8

363,363 45,475 3,757,979

1.0 0.6 9.1

380,979 46,187 4,196,718

4.8 1.6 11.7

420,094 38,291 4,174,724

10.3 17.1 0.5

468,688 35,477 4,611,113

11.6 7.3 10.5

525,526 38,493 4,791,996

12.1 8.5 3.9

Source: Hong Kong Tourism Board (1990–2002). a % in overall departures, rounded to one decimal. b Excluding departures to mainland China and Macau.

aspects of consumer behavior: notably consumer attitude, perception, preference and the decision-making process. Crompton (1977) suggested a two-stage model to describe a tourist’s destination choice process which emphasized the roles of perceived situational variables and destination image. In Crompton’s study, destination choice behavior was characterized as being a function of the interaction between perceived constraints such as time, money, travel ability and destination image. He suggested that destination images were first prioritized in terms of ideal preference and the prioritization was then amended by the impact of perceived constraints. Typically, decision-making and destination choice models in tourism examined which destination to visit in a given year. Um and Crompton (1992) viewed this choice as being propelled forward to its logical outcome by a series of travel facilitators and inhibitors. Similarly, Fakeye and Crompton (1991) viewed the destination choice process as the formation of alternative destination images until the ideal one emerges and is thus chosen. Woodside and Lysonski (1989) took a similar approach but included such variables as affective and situational factors in the destination choice process. In general, these models emphasized an incremental and sequential learning perspective based on cognition and rational cost/benefit evaluation models. For example, Assael (1987) stated that complex decision-making began with need arousal, progressed to information processing and brand evaluation, followed with purchase and concluded with post-purchase evaluation. The fundamental premise of these models is that all destination information processing follows from need recognition and that choices are evaluated and eliminated on a rational basis (Um & Crompton, 1992). The ultimate destination selected will be ‘‘ideal’’ (Fakeye & Crompton, 1991). According to the tourism literature and related models of destination choice and the decision-making

process, the general model of traveler destination choice was used as a conceptual basis for the study. In the context of tourism, Crompton (1977) suggested that destination choice should be conceptualized as being a function of the interaction between pragmatic constraints such as time, money, skills and destination images. The proposition that tourism marketing and consumer policy should be based on consumer perceptions and preferences (Van Raaij, 1986) has received substantial support. At the root of every destination choice is the assignment of utility values to various ‘‘parts’’ of the destination alternative. These parts are referred to as ‘‘destination attributes’’ (Claxton, 1989). The set of attributes is constructed in the tourist’s mind as a result of perceived needs and expectations derived from a given destination, constraints to be faced, and the information collected while pursuing a destinationchoice process. Each attribute within this set is assigned with either a positive or negative utility value. Claxton believed that once the perceived attributes and utilities have been structured by the individual, a measurement scale needs to be constructed that enables the weighting of the utility values of each attribute. This preference scale, together with a decision criterion, forms the basis of the alternative selection process. Some researchers suggested that the more attributes representing high utility values that exist in a particular alternative, the more likely that this alternative will be chosen as the preferred one. The specific destination attributes selected for this study were derived from previous destination choice related studies conducted by Gearing, Swart, and Var (1974), Ritchie and Zins (1978), Mok and Armstrong (1995), and Sirakaya, McLellan, and Uysal (1996). Besides, additional attribute of language barriers was added in consideration that selection of the

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tourism destination was made in an international context. Most image formation and destination selection models have incorporated sociodemographic variables as conventional consumer characteristics influencing perceptions of objects, products, and destinations (Friedmann & Lessig, 1986; Stabler, 1990; Um & Crompton, 1990; Woodside & Lysonski, 1989). The consumer behavior models of Fisk (1961–1962) and Sheth (1983) also recognized the sociodemographic characteristics of consumers as determinants of consumer image by including them as antecedents to cognitive processing. Although such variables as age, education, income, gender, occupation, and marital status have all been suggested as influencing perceptions and images, age and education appear to be major determinants of image. Past studies implied that the demographic background of customers and their preferences in destination choice are closely related. The more educated the tourist, the more information sources he or she will use. This showed that different education levels of tourists use different information and may have different preferences in selecting travel destinations. According to the study of Mok and Armstrong (1995), they found that the relationship between Hong Kong residents’ perceived importance of destination attributes and their demographic characteristics was closely related to a certain extent. Their study found that male respondents perceived entertainment and climate as more important than females and the elder tourists rated cultural interests and scenic beauty as more important, etc. This indicated that consumer preferences in destination choice, to some extent, are affected by their demographic background.

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test the reliability and internal consistency of importance attributes selected. The results showed that the alpha coefficients for all attributes were high, ranging from 0.87 to 0.90, well above the minimum value of 0.5 which is considered acceptable as an indication of reliability (Nunnally, 1997). 3.2. Sampling plan The target population of the study were Hong Kong residents aged 18-years old or above, who has visited one of five travel agencies at the Star House, and intended to take a leisure trip within next two years. The survey was conducted outside five travel agencies in Star House from 13th to 20th February 1999. A personal interview was used and convenience sampling employed to select the respondents. Every fifth person who came out each of the travel agencies was selected. Three hundred and seventy four people were approached for the interview and 292 interviews were completed representing a response rate of 78%. In order to see how representative the survey sample was, the Hong Kong Outbound Survey conducted through a random telephone survey by the Hong Kong Polytechnic University annually was cross checked as shown in Table 2. As indicated in Table 2, some demographic results of the survey are similar to those of the Hong Kong Outbound Survey. For example, the gender for the survey was 45.9% male and 54.1% female whereas the gender from the Hong Kong Outbound Survey were 47.3% male and 52.7 female. 3.3. Data analysis

3. Methods A quantitative approach was used in the study to find out the importance of the destination attributes that Hong Kong residents considered when choosing a travel destination. 3.1. Instrument The questionnaire was developed to collect the primary data on the preferences of leisure travel destination choice, travel characteristics, importance of travel information source and demographic variables of Hong Kong residents. A pilot test was undertaken with a small group of 20 Hong Kong residents. The results of the pilot test provided valuable information on the questionnaire design, wording and reliability of measurement scales. A reliability analysis (Cronbach’s alpha) was performed to

The frequency, mean and standard deviation were employed to assess respondents’ preferences of destination choice in terms of the destination attributes, preferences in travel characteristics, and the demographic profile of the respondents. The mean and standard deviation were also used to compare the overall ranking in the 31 destination attributes. Factor analysis was employed to combine the 31 destination attributes into factors. Reliability analysis was used to test the internal consistency of the condensed factors. Independent sample t-test and analysis of variance (ANOVA) were employed to determine whether there were any significant mean differences among the respondents with different demographic backgrounds in rating the importance of the destination dimensions (factors). These statistical tests can determine whether there is a significant relationship between respondents’ demographic variables and their travel preferences of leisure destination choice.

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Table 2 The distributions of demographic profile of respondents (n ¼ 292)

Table 3 Travel characteristics of the respondents (n ¼ 292)

Demographics

Travel characteristics

%

Mode of Travel All inclusive package Basic package tour (Hotel+Air-ticket) Independent travel (non-package tour)

65.1 8.2 26.7

Preferred Companion Yourself only Parents, brothers or sisters Spouse or children Friends Colleagues Others

6.2 7.5 45.9 35.6 4.8 0

Preferred Party Size 1 person 2–4 persons More than 4

5.5 78.4 16.1

Preferred Length of Travel 3–6 days 7–10 days More than 10 days

20.5 62.3 17.2

Gender Male Female Age 18–25 26–35 36–45 46–55 56 or above Life-Cycle Stage (Family Life-Cycle) Single-dependent on parent Single-independent Single-with child/children Married-with no child/children Married-with dependent child/children Married-with grown up child/children Others Education Level Primary level or below Secondary High School Community College/Technical Institute University or above Annual Personal Income (US $) $14,999 or below $15,000–$19,999 $20,000–$24,999 $25,000–$29,999 $30,000 or above

% (Own Survey)

45.9 54.1

30.8 22.6 24.7 10.3 11.6

% (HK Outbound Survey) 47.3 52.7

11.8 26.1 31.2 15.9 14.9 —

16.4 27.4 2.1 7.5 32.2 14.4 0

11.0 56.2 6.2 5.4

34.7 42.9 7.7 —

21.2

14.8 —

29.4 18.5 30.2 11.6 10.3

Note: The terms of life-cycle stage and family life-cycle were used interchangeably throughout the study—data not available from the HK Outbound Survey.

4. Results 4.1. Respondents’ demographic profile The respondents’ profile is presented in Table 2. The gender of the respondents was evenly distributed, with 46% male and 54% female. Regarding age, most of the respondents were under 45-years old (78%) and some respondents were older than 45 (22%). Some 46% of respondents were single and 54% were married. Married with dependent child or children were the biggest groups which constituted 32% of the respondents. Most of the respondents were the secondary school graduates (56%) or the university graduates (21%), and only 11% of the respondents were primary or below. Most respondents (78%) had annual personal income US$25,000 or less

and 22% of respondents had annual personal income over US$25,000. 4.2. Travel characteristics Table 3 shows that majority of the respondents preferred to join all inclusive package tour (65%), travel with spouse or children or friends (82%), have party size of two to four (78%), spend seven to ten days (62%) for the overseas leisure vacation. Only a few respondents (6%) preferred a party size of one, traveling on a basic package tour (8%), with parents, brothers or sisters (8%) and stayed more than 10 days (17%). 4.3. The importance of destination selection attributes The survey indicate that Hong Kong residents perceived epidemics (mean=4.6) as the most important attribute when choosing a destination for leisure travel followed by safety (mean=4.5), disaster (mean=4.4), good value for money (mean=4.3), political and social environments (mean=4.2), availability of accommodation (mean=4.2), quality of accommodation (mean=4.2), availability of transportation (mean=4.1), scenic attractions (mean=4.1), cost of trip (mean=4.1), quality of food (mean=4.1), quality of transportation (mean=4.0) and climate (mean=4.0). All 13 attributes’ means were above 4.00. The remaining twelve attributes scored between 3.00 and 4.00 and these attributes include variety of food, uniqueness of destination, shopping services and facilities, exchange rate, accessibility, publicity efforts, attitude of host community, festivals and special events, language

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barriers, entertainment and nightlife, historical sites and beaches. Recreation and sport facilities, cultural activities, destination distance from place of residence, relatives and friends at destination, hot springs and gambling scored around 2.00 (mean), meaning that they were considered as unimportant by the respondents. 4.4. Dimensions of the destination attributes Factor analysis was used to group 31 destination attributes into a set of underlying dimensions which would indicate the general concerns of the destination attributes when selecting the leisure travel destination. The 31 attributes were analyzed by factor analysis with varimax rotation to group the polarized attributes into a manageable number of factors. Six factors with eigenvalues of 1.0 or above were extracted and 24 attributes were remained under the six factors which explained 55.5% of cumulative variance in the data set. A reliability analysis, Cronbach’s alpha, was used to test the internal consistency of each factor and the factors’ overall reliability. The result indicated that the six factors were internally consistent with the Cronbach’s alpha ranging from 0.62 to 0.86. Factor 1 accounted for 16.8% of the total variation and six attributes in factor 1 were in the areas of accommodations, local transportation and food. It was labeled Tour Features. The second dimension was named as Exogenous Factor, which included attributes such as epidemics, natural disaster, safety and political and social environment. The local inherent particulars comprised the third dimension, which was termed Local Features. Six attributes were in this dimension including relatives and friends at destination, language barriers, beaches, attitudes of the host community, hot springs and gambling. The fourth dimension was about the cost of traveling overseas such as exchange rate, cost of the trip and good value for money. It was labeled Travel Cost. Dimension five was entitled Entertainment and Recreation since two attributes, entertainment and nightlife and recreation and sport facilities, were included in this dimension. The last dimension was named Special and Cultural Attractions because three attributes under this dimension were cultural activities, historical attractions and special events and traditional festivals. 4.5. Travel preferences and demographics It was found that there were significant differences between respondents’ demographic characteristics such as gender, age, marital status, education, income level and some of the destination dimensions. Statistically significant mean differences were found between respondents’ gender and two destination dimensions, Tour Features (pp0:028) and Exogenous Factors (pp0:002). Male respondents (mean=4.17) rated Tour

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Features more important than female respondents (mean=3.99) did (pp0:028). However, female respondents (mean=4.59) considered Exogenous Factors more important than male respondents did (mean=5.24) did (pp0:002). However, no significant differences were found between respondents’ gender and destination dimensions of Local Features (pp0:157), Travel Cost (pp0:188), Entertainment and Recreation (pp0:175) and Special and Cultural Attractions (pp0:594). The significant differences were found between respondents’ age and destination dimensions of Tour Features (pp0:000), Exogenous Factors (pp0:000), and Local Features (pp0:005). Respondents aged 46 or above (group 3) considered Tour Features more important than respondents aged 18–25 (group 1) and aged 26–45 (group 2). Respondents aged 26–45 (group 2) perceived this dimension more important than group 1 (aged 18–25) but less important than group 3 (aged 46 and above). The results indicated that the older the respondents were, the more important that they rated the Tour Features when selecting a travel destination. Group 2 (aged 26–45) rated the Exogenous Factors more important than group 1 (aged 18–25) and group 3 (aged 46 and above). However, the older respondents (group 3) considered the Local Features more important than the younger respondents (groups 1 and 2) did. No significant differences were found between respondents’ age and destination dimensions of Travel Cost (pp0:78), Entertainment and Recreation (pp0:303), and Special and Cultural Attractions (pp0:117). In order to manage the data in comparing the mean differences between life-cycle stage and destination dimensions, the life-cycle stage was grouped into two categories, single and married, and renamed as marital status. Two statistically significant differences were found between respondents’ marriage status and destination dimensions of Exogenous Factors (pp0:033) and Local Features (pp0:014). The married respondents (mean=4.24) considered Tour Features more important than the single respondents (mean=3.87). Both groups rated Local Feature as ‘‘Unimportant’’ to ‘‘Neutral’’. However, married respondents (mean=3.00) considered this dimension more important than the single respondents (mean=2.78). No significant differences were found between respondents’ marriage status and destination dimensions of Tour Features (pp0:749), Travel Cost (pp0:830), Entertainment and Recreation (pp0:972), and Special and Cultural Attractions (pp0:242). Respondents with different education levels were combined into three groups, Primary/below, Secondary/ High School, and College/University. Two significant mean differences were found between respondents’ education level and destination dimensions of Tour Features (pp0:006) and Local Features (pp0:004). Group 2 (Secondary/High School) rated Tour Features more important than group 3 (College/University).

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Group 1 (Primary/below) and group 2 (Secondary/High School) rated dimension of Local Features more important than group 3 (College/University). However, no significant mean differences were found between groups 1 and 2 on this dimension. This indicated that the respondents with higher education (group 3) considered Tour Features and Local Features less important than groups 1 and 2. No significant differences were found between respondents’ education level and destination dimensions of Exogenous Factors (pp0:145), Travel Cost (pp0:279), Entertainment and Recreation (pp0:658) and Special and Cultural Attractions (pp0:156). The respondents’ income levels were combined into three income groups, US$14,999 or below (group 1), US$15,000–US$29,999 (group 2) and US$30,000 or above (group 3) to test the mean differences of destination dimensions. It was found that group 3 (US$30,000 or above) considered Tour Features more important than group 1 (Under US$15,000). Group 1 rated Travel Cost more important than groups 2 and 3. Comparing groups 2 and 3, group 2 rated this dimension more important than group 3. It could be concluded that respondents with higher income perceived Travel Cost less important than those lower income groups. Both groups 1 and 3 rated Exogenous Factors more important than group 2. However, no significant differences were found between respondents’ income level and destination dimensions of Local Features (pp0:469), Entertainment and Recreation (pp0:645), and Special and Cultural Attractions (pp0:085). The Exogenous Factors that related to safety were considered as the most important dimension (mean=4.43) in selecting leisure travel destinations. Mok and Armstrong (1995) and Shih (1986) also reported similar findings in their studies. According to Plog’s (1974) psychographic continuum, Hong Kong travelers can be classified as ‘‘Near-Psychocentrics’’ who are comfort and safety-seeking, prefer a familiar atmosphere and have low activity levels. The dimension of Local Features including the relatives and friends at the destination, language barrier, beaches, attitudes of the host community, hot springs and gambling were perceived relatively unimportant for Hong Kong leisure travelers (mean=2.90). Within this dimension, gambling had the lowest mean score 2.28. This indicated that Hong Kong residents’ desire to get rest and relaxation during the trip, but gambling does not seem to be a priority during a leisure vacation.

Thus, travel marketers should emphasize this dimension in their promotional efforts. In addition, travel marketers should emphasize the safety of their organized tours and vacation image of the countries they promote. The image of safety at a particular destination cannot be determined only by the tour operators and destination marketers. All the tourism suppliers such as airlines, land operators and attraction suppliers should be involved. Co-operation of the tourism suppliers is also required to ensure the overall safety level. 5.2. Design of package tours From the marketing point of view, Sirakaya et al. (1996) suggested that the destination attributes enable the host community and destination marketer to develop and promote their tourism products more effectively by stressing the importance of each dimension according to its relative weight. When designing vacation tours, an increased awareness and possible preference for a certain destination can be created if more important dimensions can be included in a promotional message. In the research findings, apart from the Exogenous Factors, the Tour Features and Travel Cost are also important to local residents in selecting destinations. Accordingly, tour operators should emphasize these dimensions when developing their tours. 5.3. Supplementary services To survive in this competitive industry, offering supplementary services is essential to the core product. The all-inclusive package tours available in the market are similar among different tour operators. In order to create a competitive advantage from the product, additional services such as personalized consultation, free travel information and exceptional services should be offered to add value to the product. Except for safety, Hong Kong residents prefer to join the all-inclusive package tour because of convenience. These travelers have a fast pace of life and little time to plan for holiday trips. This makes the all-inclusive package tour the most preferable mode of leisure travel. As convenience is important to Hong Kong residents, tour operators should provide more convenient services to attract Hong Kong residents such as using the telephone to make reservations and provide hotlines for travel information. 5.4. Marketing strategies

5. Recommendations 5.1. Safety concern The study suggested that safety is the most important dimension for those selecting leisure travel destinations.

The preference for a specific destination may lead travel marketers to pursue either a focus strategy or a multiple segmentation strategy. A focus strategy aims at building a competitive edge and carving out a market position by catering to the specialized needs of a particular group of customers. With a focus strategy, a

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firm seeks a narrow target segment to which it may appeal. Thus, using a focus strategy in the Hong Kong outbound leisure travel market, the tour company should focus its marketing and promotional efforts on only a portion of the total market by designing an attractively priced travel package or by offering a package with a number of perceived important attributes. Unlike the focus strategy, a multiple segmentation strategy has a broader approach with the intent to serve several segments. The tour companies can then attempt to appeal to two or more well-defined segments of the market by tailoring different approaches for each specific segment. Both of these marketing strategies should emphasize the perceived important attributes in their tourism products according to their target segments.

6. Conclusion In this study, the relationship between Hong Kong residents’ preferences and demographic characteristics was examined. Results indicated that safety is the most important aspect for Hong Kong residents to select a travel destination. Furthermore, it was found that the demographic differences lead to different preferences in destination choice in terms of destination attributes. Results also showed that all-inclusive package tours are the most popular choice for the residents. Effective tourism resource management is dependent on understanding destination choice behavior. Most marketing activities associated with a tourist destination revolve around developing the destination and persuading tourists to choose that destination. A destination can be better matched to a target market’s need if resources are allocated to provide the tourist attractions which the market desires. 6.1. Limitation A few limitations of the study should also be noted. First, the sample size was relatively small (292). Due to the small sample size, sample bias might exist. Second, the survey was conducted at five travel agencies in one location. Representative bias might therefore exist. 6.2. Suggestions for future research This study examined Hong Kong residents’ preferences of destination choice in general terms. Further research might examine the preferences of destination attributes in relation to specific destinations. Therefore, further research on Hong Kong outbound leisure travelers’ behavior or their travel related characteristics

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would be useful. A segmentation analysis by clustering the sample based on the preferences might identify and evaluate viable target markets.

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