Chinese outbound tourists' perceived constraints to ...

Tourism Management 37 (2013) 136e146

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Chinese outbound tourists’ perceived constraints to visiting the United Statesq Chengting Lai, Xiang (Robert) Li*, Rich Harrill 1 School of Hotel, Restaurant, and Tourism Management, University of South Carolina, Columbia, SC 29208, USA

h i g h l i g h t s < We studied what factors constrain Chinese outbound tourists from visiting the United States. < Time and distance, security concerns, difficulty in acquiring visas, and monetary concerns were key structural constraints. < All groups that had not been to the United States indicated some negative impression of the country. < Overall, the typology portion of the Leisure Constraints Model seemed well-suited for analysis of Chinese outbound tourists.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 29 February 2012 Accepted 26 January 2013

This study attempts to gain insight into what factors constrain Chinese outbound tourists from visiting the United States, using the Leisure Constraint Model as the analytical framework. Chinese tourists who indicated low likelihood to visit the United States in the next five years were asked to explain their reasons, which were then content analyzed and categorized. The results suggest that intrapersonal and structural constraints were of particular importance for respondents, whereas few interpersonal constraints were reported. Past travel experiences and more attractive alternatives negatively affected these Chinese tourists’ intention to visit the United States. Further, the study found that time and distance constraints, security concerns, difficulty in acquiring travel visas, and monetary concerns were the main structural constraints of Chinese outbound tourists. Finally, all groups that had not been to the United States indicated that they had some negative impression of the country, which also deterred them from visiting the United States. Ó 2013 Elsevier Ltd. All rights reserved.

Keywords: Travel constraint Chinese outbound travel Leisure Constraints Model Association network

1. Introduction China has become one of the most important sources of outbound tourism in the world (Zhang, 2006). In 2011, Chinese citizens made more than 70.3 million outbound trips, a 22% increase over 2010 (He & Yang, 2012). In the Asia-Pacific region, Mainland China now ranks among the top five source markets of many countries such as Australia, Singapore, Indonesia, New Zealand, and the Philippines (Department of Tourism, 2009; Singapore Tourism Board, 2008; Statistics Indonesia, 2008; Statistics New Zealand, 2008; Tourism Australia, 2008). Most researchers believe that the Chinese outbound tourism market has much potential for future growth (Li, Harrill, Uysal, Burnett, & Zhan, 2010; Wang, 2006).

q This paper is partly based on the first author’s Master’s thesis. A portion of this study was presented at the 15th Annual Graduate Education & Graduate Student Research Conference in Hospitality & Tourism in 2010. * Corresponding author. Tel.: þ1 803 777 2764. E-mail addresses: [email protected] (C. Lai), [email protected] (X.(Robert) Li), [email protected] (R. Harrill). 1 Tel.: þ1 803 777 7682. 0261-5177/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tourman.2013.01.014

Understanding Chinese tourists is an essential step toward success in the China market, especially for destinations like the United States, which has only recently started marketing to Mainland China. It has been suggested that understanding travelers’ decisionmaking requires understanding both positive (e.g., motivational) and negative (e.g., constraining) factors affecting their decisions (Jackson, 2005). However, travel constraint has drawn comparatively less attention in the tourism literature. In early research, constraints were initially viewed as barriers, before researchers realized the role of negotiation in leisure and travel participation (Hubbard & Mannell, 2001; Jackson, 2005; Nyaupane & Andereck, 2008). Understanding the reasons why tourists do not travel is important because it helps marketers develop products and strategies. It also helps forecast tourism demand (Gilbert & Hudson, 2000). However, most studies on travel constraints have been conceived within the Western positivist tradition, emphasizing the social and psychological characteristics of travel constraints while in some cases ignoring individual perspectives and experiences as well as cultural and political dimensions (Chick & Dong, 2005; Dong & Chick, 2012).

C. Lai et al. / Tourism Management 37 (2013) 136e146

Conceptually, the most dominant theoretical framework for travel constraints has been Crawford, Jackson, and Godbey (1991) Leisure Constraints Model (LCM). Rarely have non-Western tourists’ travel constraints been studied under this model. Thus, the purpose of this study was threefold, including: (1) examining the constraints of Chinese outbound tourists; (2) exploring the usefulness of the LCM (Crawford et al., 1991) in a non-Western context; and (3) understanding how constraints differ by travel experiences. 2. Literature review 2.1. The Leisure Constraint Model (LCM) and studies on travel constraints When discussing reasons why people avoid certain behaviors, some researchers have employed, along with the word “constraint,” terms such as “risk” (Moutinho, 1987) and “inhibitors” (Um & Crompton, 1992), but the underlying meanings of these terms are very similar. Jackson and Scott (1999, p. 301) defined constraints as factors that “limit people’s participation in leisure activities,

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people’s use of leisure services, or people’s enjoyment of current activities.” Wade and Hoover (1985) suggested that constraints tend to affect people’s ability to be involved in leisure activities (see Table 1 for a summary of selected studies). In 1987, Crawford and Godbey (1987) first introduced the LCM with three types of constraints: intrapersonal, interpersonal, and structural (Hudson & Gilbert, 2000; Nyaupane & Andereck, 2008). Later, Crawford et al. (1991) proposed that the three types of constraints are hierarchically ordered by importance, and participation in leisure activities requires overcoming each level of constraints in succession (Fredman & Heberlein, 2005; Hudson & Gilbert, 2000). According to the LCM, intrapersonal constraintsdthe first level of the modeldrefer to individual psychological states and attributes, such as lack of interest, stress, depression, anxiety, religiosity, and perceived self-skill, that interact with leisure preferences (Crawford et al., 1991; Fredman & Heberlein, 2005; Nyaupane & Andereck, 2008). Intrapersonal constraints are the most powerful and intimate of the three types of constraints (Carroll & Alexandris, 1997; Crawford el al., 1991; Iso-Ahola & Mannell, 1985). The next level of the model is interpersonal constraints, which result from

Table 1 Selected studies on travel constraints. Author

Year

Sample

Studied items

Important constraints

Shin

1998

College students in the U.S.

Lack of information Lack of interest Distance/Difficulty of access Financial resources Lack of time and work obligations Ability and social Planning and lack of transportation Ability of travel opportunity Social status

The following variables are important in both early and late considerations of destination: Money is major factor in travel decision Amount of time available High cost of trip Travel expenses compete with other use of money

Fleischer and Pizam

2002

Israeli seniors

Age Health Organization Education Religious industry Gender Income Marital status Continuity

Self-assessed non-healthy condition Low level of income

Hudson

2000

Health club chain members in England

10 items of intrapersonal constraints 10 items of interpersonal constraints 10 items of structural constrains

The following constraints are important in both men and women’s decision-making Anticipation of expense Clothing and equipment are too expensive Lack of low-cost, all-inclusive holidays

Pennington-Gray and Kerstetter

2002

U.S.A. adults

Demographic variables 3 items of intrapersonal constraints 3 items of interpersonal constraints 5 items of structural constraints

Money Time Weather

Nyaupane et al.

2004

U.S.A individuals

5 items of intrapersonal constraints 2 items of interpersonal constraints 6 items of structural constrains

The following constraints are important in participating 3 kinds of activities: Have no time to go Family commitments Family and friends are not interested

Fredman and Herberlein

2005

Swedish residents

Income Children under 18 Number of leisure activities Number of other trips Distance Friends in activity Age Health problems Self-perceived skill

Distance Income

Nyaupane and Andereck

2008

Arizona residents and out-of-state residents

Demographic variables 5 items of intrapersonal constraints 4 items of interpersonal constraints 10 items of structural constraint

Time Cost

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social interaction or the relationships between individuals’ characteristics. For example, individuals may confront interpersonal constraints when they are unable to find travel partners (Crawford et al., 1991; Fredman & Heberlein, 2005; Hudson & Gilbert, 2000). The third level of the LCM is structural constraints, which are formed after leisure preferences are developed, but before actual leisure participation. Structural constraints may intervene between leisure preferences and participation. Examples of structural constraints include lack of time, money, information, and access, as well as seasonality (Crawford et al., 1991; Hudson & Gilbert, 2000; Nyaupane & Andereck, 2008). Although the LCM was developed to explain people’s constraints when participating in leisure activities, researchers have tested it on travel behavior. Goodale and Witt (1990) applied constraintresearch findings to tourism, showing how the LCM may be relevant to destination marketing. Several subsequent tourism studies have also supported LCM (e.g., Nyaupane, Morais, & Graefe, 2004; Penningtom-Gray & Kerstetter, 2002). Of the LCM’s three constraint levels, structural constraints have been researched the most. A classification of structural constraints specific to outdoor recreation was developed by Walker and Virden (2005), including natural and environmental constraints, social environment structural constraints, territorial structural constraints, and institutional structural constraints (Shores, Scott, & Floyd, 2007; Walker & Virden, 2005). In a tourism context, Nyaupane and Andereck (2008) revealed three distinctive subdimensions within the structural constraints construct, respectively relating to place, time, and cost. Of these three constraints, they found that time and cost tend to be more difficult to overcome, but once these two are cleared, factors related to place (i.e., travel destination) become less important. Several studies have emphasized constraint differences based on market segmentation, including sociodemographic factors. Hudson (2000) found that male and female skiers perceive constraints differently, with women perceiving higher levels of intrapersonal constraints than do men. Nyaupane and Andereck (2008) also found that the effect of structural constraints differs by sociodemographic factors. For instance, cost is more of a concern for travelers aged either below 30 or above 70, while time is a more critical constraining factor for the middle ages. With regard to nature-based tourism activities, Nyaupane et al. (2004) found significant differences in the role of intrapersonal constraints among different activities, including whitewater rafting, flatwater canoeing, and horseback riding. Penningtom-Gray and Kerstetter (2002) also examined the three types of constraints as applied to naturebased tourism, finding that constraints change with age and family life stage. Similarly, Fleischer and Pizam (2002) also found constraint differences with regard to age. All above studies were primarily conducted in Western, particularly North American, contexts. Chick and Dong (2003) raised concerns that the LCM might not be applicable to non-Western cultures and hence refined the model to include a fourth level termed “cultural constraints.” More broadly, Iwasaki, Nishino, Onda, and Bowling (2007) suggested that researchers may face a paradigm mismatch when applying Western-based theories to an Asian context. Thus, it would be interesting to empirically examine if the LCM is applicable or not to an Asian context. 2.2. Travel behavior of Chinese outbound tourists Due to the diversity of history and culture, people from different countries may exhibit substantially different behaviors. Hofestede’s (2001) study, based on his model of five cultural dimensions, showed different scores between Asian and non-Asian countries illustrating the significant cultural differences between these

countries. It seems logical to infer that travel constraints may vary considerably across nationalities and cultures. For example, interviews conducted by Chick and Dong (2003) in Japan and China indicated that culture influences travel constraints. Accordingly, it may be reasonable to surmise that these same differences exist between Western and non-Western countries. The rapid development of China’s outbound tourism has drawn worldwide research attention, mainly in the area of travel motivations (e.g., Hsu & Lam, 2003; Huang & Hsu, 2005; Jiao, 2003; Lau, 2005; Li, 2008). In contrast, constraint research on Chinese outbound tourism is relatively sparse. Zhou, King, and Turner (1998) found that the difficulty in obtaining entry visas often has proved to be an insurmountable structural constraint to the growth of Chinese outbound travel demand. Conversely, seeing famous attractions has served as a primary motivation for Chinese outbound tourists. Following the pushepull model, Hsu and Lam (2003) found that the top five factors inhibiting Mainland Chinese from visiting Hong Kong were cost, lack of travel agencies, short holidays, difficulty in obtaining travel documents, and safety. Huang and Hsu (2005) confirmed the findings of Hsu and Lam (2003) through focus groups conducted under the same guiding theory. Huang (2007) used the LCM when exploring the effects of motivation, past experience, attitude, and constraints on tourists’ intention to revisit. He found that neither structural nor intrapersonal constraints have a significant effect on revisit intention, but disinterest (an intrapersonal constraint) had a very strong negative effect on revisit intention. Li (2008) also used the pushepull model to examine the travel constraints of Chinese outbound tourists, revealing the top five travel constraints as high expense, work commitment, too much housework, low return on the trip versus money spent, and low expectation on satisfaction or selfactualization. Similar to Zhou et al. (1998), Li (2008) also found difficulty in obtaining an entry visa to be a major travel barrier for Chinese tourists, and long-haul outbound travelers are more challenged by this constraint than short-haul travelers. Li (2008)’s findings also suggested that constraints differ by age, gender, education, occupation, and income, while motivations differ by age, education, occupation, and income. More recently, Sparks and Pan (2009) explored the attitudes, constraints, and information sources of Chinese outbound tourists based on the Theory of Planned Behavior. They found that safety concerns and external barriers (e.g., exchange rate, flight time, cost, language, visa regulations, and media warnings)dall being structural constraints, influence travel intentions substantially. Note, in most of the aforementioned studies, travel constraints were not the research focus. Indeed, few studies have systematically examined Chinese tourists’ outbound travel constraints, and even fewer analyzed Chinese tourists’ travel constraints based on the LCMda theoretical gap already identified in previous reviews of the LCM. Hence, the purpose of this study was to examine the utility of LCM in an Asian tourism context. Considering the exploratory nature of this study, and the potential paradigm mismatch when applying a Western-originated theory in a non-Western context (Iwasaki et al., 2007), the authors decided to take a qualitative approach. Dong and Chick (2012) suggest that leisure constraint items or ideas are highly culture-, context-, and population-specific, so simply borrowing constraint items from previous studies is not the ideal way of measuring travel constraints in a non-Western context. Thus, the authors used open-ended questions to solicit responses, and then analyzed the data qualitatively. 3. Methods This study was a part of a larger project on Chinese outbound tourism conducted from an American perspective. A questionnaire


survey was conducted via face-to-face interviews with 1600 respondents. These individuals were selected in three major outbound-tourist-generating citiesdBeijing, Shanghai, and Guangzhou (CTC, 2007; WTO, 2003). As centers of China’s three primary tourist-generating markets respectively, these three cities not only record the highest outbound travel incidence, but also set the trends for the entire Chinese outbound travel market (Arlt, 2006; Li et al., 2010). Convenience sampling methods such as networking, referral, and intercepts were adopted in this study, due to the welldocumented challenges in probability sampling in the Chinese outbound travel market (Roy, Walters, & Luk, 2001). Following Li et al. (2010), the respondents were classified into four groups based on their travel experience. Group 1 consisted of respondents who had traveled to the United States in the past three years; Group 2 consisted of those who had traveled outside Asia (other than the United States) in the past three years; Group 3 consisted of those who had traveled within Asia in the past three years, but would like to visit outside Asia in the next two years; and Group 4 consisted of those who had not traveled outside China in the past three years, but would like to travel outside Asia in the next two years. Each group had 400 respondents. These four groups may be viewed as four common-sense segments of the current Chinese outbound travel market. The one-on-one interviews were conducted in Chinese by a professional marketing company. The respondents were asked about their travel attitudes, travel experiences, perceptions of the United States, travel intentions, and demographic information. Those respondents who were not likely to travel to the United States in the next five years were asked to provide up to three reasons for their response (i.e., “What is the main reason you are not interested in traveling to the U.S. in the next five years?”). The open-ended responses were the main data set in this study. In preparation of qualitative data analysis, a codebook was developed in Chinese following a four-step process: (1) Twenty percent of responses were prelisted verbatim in Chinese; (2) Based on these phrases, the first draft of the codebook was formulated by categorizing the phrases and coding all the categories; (3) All responses were coded using this draft of the codebook, with multiple revisits and revisions throughout this process; and (4) After all the responses were coded, the final version of the Chinese codebook was prepared. Finally, the codebook was translated into English. After that, the authors translated each response based on the codebook. To be true to the original responses, the authors used word-by-word translation. Thus, some of the terms may not be entirely consistent with the American language usage. Frequency analysis by SPSS software was used to understand the respondent sample profile, and content analysis by CatPac software was used to provide structure to constraints by categorizing and clustering them (Kassarjian, 1977; Stepchenkova, Kirilenko, & Morrison, 2009). CatPac software analyzes the relationship of frequently occurring words in textual data using concordance analysis and stores the results as an artificial neural network. A part of the CatPac software, Oresme, was used to simulate the associative thinking process of the respondents using the artificial neural network built from the responses. Oresme computes which keywords are associated to a given input set of keywords. All keywords were sent to Oresme, in turn, and the associated keywords for each one were calculated and recorded to make an association network graph. Another component of CatPac, Thought View, visualized the relationship among constraints by plotting keywords in two- or three-dimensional coordinates. From this plot, clusters of keywords were visualized and categorized.

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4. Results and findings 4.1. Respondent profile As designed, the sample was equally distributed among the three cities: 532 from Beijing, 532 from Shanghai, and 536 from Guangzhou. The gender distribution was fairly even, with 55 percent being male. Almost half (49.5%) of the respondents were middle-aged (35e64). Young adults (20e34) accounted for 40.9% of the sample, whereas senior adults (65 or above) accounted for 7.7%. Approximately 67.1% of the respondents had a monthly household income between RMBU 2000e19,999 (about US$294e$2941), which is roughly China’s middle-class income range (Liu, 2006) (Table 2). When the respondents were asked how likely they were to visit the United States in the next five years, 348 respondents were “not too likely” or “not at all likely” to do so, whereas 1176 respondents reported they were “somewhat likely,” “very likely,” and “definitely going” to visit the United States. The high travel intention was not surprising considering that the study’s target group comprised past or potential long-haul outbound travelers. For the purpose of this study, the rest of the analysis focused on the 348 respondents with low propensity to visit the United States, presumably because of travel constraints. Interestingly, nearly half (46.8%) of the 348 respondents were from Guangzhou, while the rest were an equal split between Beijing (27%) and Shanghai (26.1%). As expected, Group 1 (i.e., respondents who had traveled to the United States in the past three years) was overrepresented (33%) among these 348 respondents, with Groups 2, 3, and 4, respectively, accounting for 24.4%, 22.4%, and 20.1% of this sample. Their demographic profile is listed in Table 2. 4.2. Overall analysis Six hundred and thirty-six responses were obtained from the 348 respondents on constraints, with each respondent providing 1.83 responses on average. A total of 1478 words were used in the constraint data set, and the authors chose the top 30 most frequent words as keywords for analysis by CatPac (see Table 3 for a list). Fig. 1 shows the association network among the constraint keywords generated using Oresme. Overall, “not convenient to get a visa,” “not enough disposable income,” and “terrorist incidents” were connected most frequently with other constraints (11 times each), indicating their central role in the network. Further, it appeared certain constraints tended to remind respondents of other constraints (i.e., most arrows start from them), implying a more salient status in respondents’ cognitive system. These included “want to travel to other countries,” “have been there before,” “not enough disposable income,” “far away,” and “lacking security.” On the other hand, some other constraints, including “not convenient to get a visa,” “old,” and “terrorist incidents,” appeared more in the receiving end of the associations, implying they were more likely to be activated or associated after other constraints were recognized. “Old,” “not convenient to get a visa,” and “terrorist incidents” were associated with each other, implying they were usually thought of concurrently by respondents. This could suggest that senior Chinese tourists are more likely to be constrained by the visa and terrorism issues when considering traveling to the United States. Notably, “far away” was associated with “old,” implying that long travel distance reminded some respondents of their physical infirmities. Also, “not enough disposable income” was associated with “high price levels” (Chinese respondents call that “high consumption level”), but “high price levels” was not associated with “not enough disposable income.” This indicated that even some of

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Table 2 Respondents’ demographic profile. Demographics

Gender Age

Education

Employment status

Monthly household income (RMB)

Male Female 18e19 20e29 30e39 40e49 50e64 65þ High school or less Technical/vocational high school Some college College degree Graduate school/advanced degree Employed full-time/part-time Housewife/homemaker Temporarily unemployed/looking for work Retired Student Below 2000 ( ¼ USD$7353)

The whole sample (N ¼ 1600)

The “no interest” subsample (N ¼ 348)

Total

%

Total

%

885 715 31 388 500 297 261 123 316 166 502 517 75 1274 44 26 146 79 14 62 244 329 406 193 113 79 111

55.3 44.7 1.9 24.3 31.3 18.6 16.3 7.7 20.1 10.5 31.9 32.8 4.8 81.2 2.8 1.7 9.3 5.0 0.9 4.0 15.7 21.2 26.2 12.4 7.3 5.1 7.2

193 155 7 73 97 66 59 46 73 50 124 88 11 259 7 10 47 20 0 17 42 82 92 53 14 14 23

55.5 44.5 2.0 21.0 27.9 19.0 17.0 13.2 21.1 14.5 35.8 25.4 3.2 75.5 2.0 2.9 13.7 5.8 0 5.0 12.5 24.3 27.3 15.7 4.2 4.2 6.8

the relatively wealthy respondents were concerned with the price levels, because respondents who mentioned “high price levels” did not necessarily mention “not enough disposable income.” Another interesting finding was that when respondents thought of terrorist attacks, they did not associate that with “lacking security,” but respondents who thought of “lacking security” did connect it to “terrorist incidents,” as shown by the directional association. This illustrates that security is a broad issue which includes terrorism as well as other concerns such as violence, lawlessness, gun control, and accidents. However, “lacking security” and “terrorist incidents” were both linked to “far away,” indicating that distance evoked concerns about security and terrorism.

From the three-dimensional conceptual map made by Thought View, keywords were clustered into nine groups, and nine themes emerged. The keyword clusters, themes, and constraints categories are shown in Fig. 2. For example, the keywords “lacking,” “security,” and “incidents” were clustered into the theme of “lacking security”; the relationship between these keywords in the association network supported this clustering. “Have been there before,” “want to travel to other countries,” and “too old to travel” were classified as intrapersonal constraints, because they arose from the psychological state of the respondents; the first two factors implied the respondents’ lack of interest in the United States. Consistent with the literature, “have no time”

Table 3 Descending frequency list of keywords from responses on travel constraints. WORD

FREQUENCY

PERCENTAGE

CASE FREQUENCY

CASE PERCENTAGE

NOT HIGH CONSUMPTION BEEN NO TRAVEL US THERE BEFORE LACKING SECURITY TIME ENOUGH WANT DISPOSABLE INCOME COUNTRIES VISA CONVENIENT

164 107 105 79 75 72 71 70 66 64 64 58 55 51 48 47 36 34 33

10.6 6.9 6.8 5.1 4.9 4.7 4.6 4.5 4.3 4.1 4.1 3.8 3.6 3.3 3.1 3.0 2.3 2.2 2.1

887 655 646 433 453 449 394 404 371 383 377 358 354 333 313 305 248 228 221

57.7 42.6 42.0 28.2 29.5 29.2 25.6 26.3 24.1 24.9 24.5 23.3 23.0 21.7 20.4 19.8 16.1 14.8 14.4 Fig. 1. The association network for all responses on constraints.


Keywords from CatPac been, there, other countries, before, travel, want

Emerging Themes Have been there before Want to travel to other countries

Intrapersonal constraints

old Too old to travel have, no, time Have no time lacking, security

Interpersonal constraints

Lacking security incidents get, visa, convenient far, away high, consumption not, enough, disposable

Not convenient to get a visa Far away

Structural constraints

High price levels Not enough disposable income

Fig. 2. Keyword clusters, themes, and constraint categories for all responses.

(Nyaupane & Andereck, 2008; Penningtom-Gray & Kerstetter, 2002; Shin, 1998), “far away” (Fredman & Heberlein, 2005), “high price levels,” (Nyaupane & Andereck, 2008; Shin, 1998), and “not enough disposable income” (Fleischer & Pizam, 2002) were classified as structural constraints; “lacking security” and “not convenient to get a visa” were also structural constraints found in the responses (Hsu & Lam, 2003; Sparks & Pan, 2009). Surprisingly, unlike the study by Nyaupane et al. (2004), interpersonal constraints were less emphasized. Although some respondents mentioned “no relatives in the United States” and “no business in the United States,” keywords relating interpersonal constraints occurred so infrequently that they were not among the top 30. 4.3. Group-based comparison Similar to Fig. 2, a series of figures for the four sample groups were developed depicting keyword clusters, themes, and associated constraint categories. Due to space limitations, these figures will not be reported here but are available upon request. For those respondents who had been to the United States before (Group 1), “have been there before” was a significant intrapersonal constraint. Some also responded that “age” and “poor health” were inhibiting their revisit intention. “Age” (or being “old”) was also reported by Group 2 respondents as a key constraint, but not by the two other groups. The intrapersonal constraint of the respondents who had traveled internationally within Asia (Group 3) and potential outbound tourists (Group 4) were different from the other two groups in one key aspect: they emphasized “want to visit other countries.” All groups that had not traveled to the United States before (Groups 2, 3 and 4) mentioned the constraint “bad impression”; some Group 4 respondents also indicated concern over Americans being inhospitable. Some respondents who had been outside of Asia (Group 2) thought the United States was “chaotic” (in the Chinese language, this connotes danger, lawlessness, and immorality). An interesting finding was that only the potential outbound tourists (Group 4) emphasized interpersonal constraints, and they mentioned the least structural constraints among the four groups; those respondents who had been on outbound trips within Asia (Group 3) mentioned the most structural constraints. “Lacking security,” “have no time,” “not enough disposable income,” and “high price levels” were emphasized by all four groups. The respondents in Groups 2, 3, and 4 also emphasized the keywords “terrorist” and

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“incidents,” which illustrated their security concerns. The potential outbound tourists (Group 4) seemed to take this factor relatively seriously. Besides the keywords “terrorist” and “incidents,” they also emphasized “violence.” The respondents who had traveled abroad before (Groups 1, 2, and 3) were concerned about acquiring visas and facing time constraints. Those who had taken outbound trips but not to the United States (Groups 2 and 3) also mentioned the long travel distance as a constraint. Both Groups 3 and 4 emphasized the language barrier as a constraint. Group 3’s emphasis of this constraint is understandable because, in contrast to countries outside of Asia, language is less a concern in some Asian countries, especially those in Southeast Asia. Table 4 summarizes the above findings. Figs. 3e6 showed more detailed association networks of the keywords for each group. One keyword is set active (all others inactive) and the activation is spread through the artificial neural network built by CatPac. Any words that are activated by more than 0.10 due to this process are connected on the network graph. When the activation index, the numerical label on each link, between A and B is larger than 0, B is activated by A. This means that when the keyword A is set active (but no other keywords are set active), activation spreading through the artificial neural network sets B active. Note that B may not be set active if other nodes than A are active, because other nodes may have an inhibitory effect on B. However, the larger the activation index between A and B, the stronger the connection, meaning that even in the presence of other active keywords, B is more likely to be active. In the four association networks, the network for past U.S. travelers has the most links and nodes (24 links between 10 nodes, 2.4 links per node, see Fig. 3), and the network for Group 4 travelers has the least links and nodes (13 links between 8 nodes, 1.625 links per node, see Fig. 6). The presence of few links indicates that most of the connections are weak (activation index is smaller than 0.1). The large number of links per node for the network of the pastU.S.-travelers group indicates that these travelers’ constraint keywords are frequently associated with each other (Fig. 3). Consistent with the keyword clusters, the node “poor health” only shows up in this group, and it also has strong connections with “not enough disposable income,” “lacking security,” and “far away.” For those who had traveled outside of Asia (Fig. 4), the node “chaotic” is particular to this group, and it has medium-strength connections with “incidents” and “bad.” When “bad” is activated, the respondents are likely to think of “incidents,” “chaotic,” “high consumption,” “time,” “impression,” “enough disposable income,” and “convenient visa.” In this graph for respondents who had traveled to other Asia destinations (Fig. 5), “enough” and “disposable income” are not in the same node; this was because the respondents mentioned “not enough time” instead of “have no time,” so “enough” is also closely connected with “time” in addition to “income.” When “bad” is activated, the node “language barrier” is likely to be turned on. For the potential travelers group (Fig. 6), the node “relatives” shows up only in this group. When “bad” is activated, “language barrier,” “relatives,” and “lacking security” are activated. Consistent with the keyword clusters, the node “language barrier” appears only in the graphs for Group 3 and Group 4. 5. Conclusions and discussion The Leisure Constraint Model (LCM) (Crawford el al., 1991) proposes the existence of three types of constraint: intrapersonal, interpersonal, and structural. This study found that intrapersonal and structural constraints were of particular importance for Chinese outbound tourists. In comparison, relatively fewer interpersonal constraints were reported by respondents. Past travel

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Table 4 Chinese outbound travelers’ key constraints to visit America: A summary.

Intrapersonal constraints

Interpersonal constraints Structural constraints

Group 1

Group 2

Group 3

Group 4

All

Have been there before;

Too old to travel Bad impression

Want to travel to other countries Bad impression

Have been there before;

Too old or unhealthy to travel

Want to travel to other countries Bad impression

e

e

e

Far away; Lacking security; Have no time;

Far away; Lacking security; Not convenient to get a visa; High price levels;

Far away; Lacking security; Not convenient to get a visa; High price levels;

Not enough disposable income Have no time

Not enough disposable income Have no time Language barrier

Not convenient to get a visa; High price levels; Not enough disposable income

experiences and more attractive alternatives negatively affected their intention to visit the United States. Time and distance constraints, security concerns, difficulty in acquiring travel visas, and monetary concerns (i.e., high price levels at the destination and not enough disposable income) were found to be the key structural constraints of Chinese outbound tourists in the study. Language barrier was reported to be a structural constraint by lessexperienced tourists. Notably, in this study only potential outbound tourists emphasized interpersonal constraints such as “have no relatives in the United States.” Finally, all groups that had not been to the United States indicated that they had some negative impression of the country, and the bad impressions seemed to have affected their travel intentions. Overall, the typology portion of the LCM seemed well-suited for analysis of Chinese outbound tourists as all the constraints by respondents could easily be categorized within the model. The

Have no relatives in the U.S. Lacking security; High price levels; Not enough disposable income Have no time Language barrier

Want to travel to other countries Too old to travel e Have no time; Lacking security; Not convenient to get a visa; Far away; High price levels; Not enough disposable income

constraints of time, cost, distance, and travel inconvenience due to health reasons were consistent with prior research on Western tourists (Fleischer & Pizam, 2002; Fredman & Heberlein, 2005; Hudson, 2000; Nyaupane & Andereck, 2008; Penningtom-Gray & Kerstetter, 2002; Shin, 1998). Although most keyword clusters and themes were found to be similar among the four groups of respondents, the association networks show that the importance of these keywords was different for the groups. Notably, few interpersonal constraints were reported by respondents: potential travelers with no outbound travel experience mentioned “lack of travel partner” and “no relatives in the U.S.” This finding may be somewhat counterintuitive: the Chinese culture values collectivism, where travel decisions are highly related to family or group influences and group travel is generally preferred (Reisigner, 2009). One would reason that interpersonal constraints should play a more important role than the present findings

Fig. 3. The association network for Group 1 responses.


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revealed. A possible explanation is that different constraint items have different levels of accessibility in people’s minds (Fazio, Powell, & Willams, 1989; Romaniuk & Sharp, 2004), and interpersonal constraints might be less cognitively accessible than some other constraints. Specifically, one’s travel preference or behavior is usually jointly determined by a number of factors, all stored in the individual’s cognitive system in order of accessibility (Fazio et al., 1989; Romaniuk & Sharp, 2004)dsome constraints, such as lack money or time, are presumably more immediately accessible than others. When responding to questions, the respondents retrieve information from their cognitive system following this order. For this study, each respondent was allowed to provide up to three

reasons, as thus only able to report the most salient constraint items. Consequently, although many Chinese tourists may indeed be constrained by factors such as “lack of travel partner” or having “no relatives in the U.S.,” these constraints were seldom reported because of low immediate accessibility. Had the researchers probed further, more interpersonal constraints might have emerged. Another possible explanation is that behind such structural constraints as “lacking money” or “lacking time” could be interpersonal reasons. Dong and Chick (2012) recently examined Chinese citizens’ leisure constraints, and revealed interpersonal constraints such as “family issue” (e.g., “busy with child care” and “busy caring for elders”). Thus, interpersonal factors such as taking


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care of children or elders were indeed the underlying reason for “having no time,” a structural constraint. However, such in-depth information could not be easily detected by the “up to three answers” survey approach employed in this study, which should be considered as a research limitation. Of course, both explanations are speculative and future research using more sophisticated probing techniques such as laddering interviews could verify or falsify these speculations. Finally, from a cultural perspective, while the notion of collectivism may be embedded in cultural norms, the degree of self-awareness necessary to identify such norms as an intrapersonal constraint may only be found in a subset of travelers. Future research should address the cognitive dichotomy between self and group in different types of societies, and to what extent these differences may influence research. Findings of this study suggest that structural constraints in future research might be differentiated not only as domestic and international travel constraints, but also as regulatory and perceived safety constraints, e.g., actual rules that inhibit travel versus perceived barriers. For example, perceived convenience in obtaining a visa might be addressed through the streamlining of regulatory proceduresdindeed, this is a key issue the U.S. government has attempted to address lately (Bull, 2012); undoubtedly, the lifting of this perceived constraint should be communicated among potential tourists through news media and by word-of-mouth. Lack of security also connotes a highly unknown situation with no clear and immediate resolution, and may be correctly considered as beyond the control of origin and destination governments. The authors found that perceived lack of security was associated not only with terrorism, but with a wide range of negative issues, including violence and gun control. As a result, these perceptions prove to be much harder to address than destinations realize, requiring substantial and perhaps costly coordination between marketing and security programs. Keywords and terms such as “chaotic,” “terrorist incidents,” and “violence” illustrate the inherent intractability of many security issues. One might argue there is a sense of randomness to these events that may play an important role in travel planningdtrips to the embassy to obtain a visa, while long and inconvenient, may be planned for. Conversely, a random act of violence, while not necessarily affecting the traveler directly, may alter travel plans enough to introduce a significant unplanned expense in terms of time and money and therefore completely disrupt a well-planned trip. The researchers found that travelers’ age might play a role in forming negative safety perceptions, creating a marketing challenge to reach Chinese senior travelers who have the time, money, and access to international travel experiences for the first time. These are the types of perceptions that may

be the most difficult to analyze by tourism researchers, most difficult to address by travel marketers, and beyond the control of travel destinations. Both intrinsic and structural, fear of the unknown seems to have constrained travel since the beginning of human history. The results of the analysis indicate that currently American destinations should target relatively wealthy people in China as they seemed to be less affected by key structural constraints including time and monetary factors. Put differently, these are more negotiable constraints for Chinese with a higher socioeconomic status. To target this group, general advertising to the public may not be immediately effective for now. Rather, U.S. destinations and business should target Chinese tour operators, travel writers, social elites, and other opinion leaders, and then use mass communication tools mainly for awareness-building purposes. In the meantime, efforts should be made to reduce the influence of some constraints. For example, U.S. travel companies should hire Chinese-English-speaking guides to help travelers cope with the language barrier. Detailed tutorials and assistance programs can be implemented to ease the process of acquiring visas, and the availability of such programs should be emphasized in advertisements to help assuage Chinese travel concerns. Airlines should implement more direct flights, ground transportation should be streamlined, and detailed trip information and maps made accessible on the Internet to reduce the perceived travel distance and increase the perceived comfort levels of outbound tourists. One interesting finding of this study is that the group of respondents that had previously traveled to the United States did not seem to have very different structural constraints from those groups who had not, suggesting previous travel does not necessarily alter perceptions of distance or security. This illustrates that some of the constraints are hardly negotiable. For instance, geographical and cultural distances cannot be easily overcome. On the other hand, it also shows that the American travel industry still has some work to do. Bottom line, although some hard facts are not easily changeable, marketers should make sure the facts are appropriately communicated and not distorted, because poor communication will inevitably lead to misperception (e.g., the flight between China and America takes about 12e14 h, but many potential travelers interviewed for this study thought it was longer). Attracting people who have not yet visited the United States requires improving their perception of the United States (Li & Stepchenkova, 2012). Information targeted at specific causes behind negative impressions of destinations can spread via social networking websites, educational Internet-based games, travel blogs, attractive videos on video-sharing websites, and other techniques. For example, perceptions of high prices can be modified by online interfaces that allow Chinese players to experience shopping in a virtual U.S. shopping mall. The identification and retention of social marketing “influentials” may also helpdthose Chinese residents who play a central role in large social and peer groups, who are then paid to promote websites, create blogs, and participate in chats that promote U.S. tourism. Such “guerilla” marketing strategies should make some impact on international tourism destinations and brands over time. 5.1. Limitations and future research Sampling of respondents in this study was restricted to Beijing, Shanghai, and Guangzhou (i.e., Tier 1 cities), which limited the generalizability of the results with respect to the entire Chinese outbound tourism market. For future studies, some Tier II cities such as Shenzhen, Shenyang, and Tianjin should also be included, as these cities are markets with great growth potential (Li et al.,


2010). Meanwhile, although the whole sample was evenly distributed among the three cities, nearly half of this study’s final sample comes from Guangzhou. This might reflect Guangzhou’s status as the most regional one among the three cities. Alternatively, it could indicate a city- or region-specific low level of interests toward visiting the United StatesdLi et al. (2010)’s phone survey reported high overall outbound travel incidence of Guangzhou. This warrants American destination marketers’ attention. Due to its exploratory nature, this study focused on categorizing constraints following the LCM. Future research may examine and verify the hierarchy of constraints and tourists’ negotiation processes in a non-Western context. As indicated, more in-depth, sophisticated probing techniques may help decipher the underlying reasons behind the constraints, and which constraints are more negotiable from tourists’ perspective. Structured surveys may be used to ask questions under hypothetical situations in which some constraints are overcome and others are not. All these will help advance LCM toward a useful theoretical tool in explaining and predicting travelers’ decision (Godbey, Crawford, & Shen, 2010). Further, some of the findings in this study could be best explained in the Chinese cultural contexts. A formal crosscultural comparison of Chinese-versus-Western tourists’ travel constraints may also help assess cultural differences concerning constraints. In addition to China, other non-Western source markets such as India and South Korea will continue to grow in influence, altering not only balance of tourism payments and receipts but also the balance of perceptions about travel motivations and constraints. The findings here seem to support the universality of certain perceptions, such as lack of time and money, but also suggest more society-specific constraints, e.g., visa processing issues, that reflect the new realities of travelers in today’s often chaotic world, as perceived by first-time travels to the West. Researchers, marketers, and governments must redouble their efforts to provide new travelers with images of comfort and safety to induce them to travel. This information will require researchers to access deep, personal experiences embedded in dense social networks and framed by ongoing social, cultural, and political issues and events. Gradually, new models for travel behavior will emerge from these collective voices and experiences, models that may reflect the hopes and concerns of the global travel community. Acknowledgments This project is funded by the Alfred P. Sloan Foundation Travel & Tourism Industry Center at the University of South Carolina, the U.S. Department of Commerce/Office of Travel & Tourism Industries (OTTI), the U.S. Travel Association (formerly Travel Industry Association, TIA), and more than 20 U.S. destination and travel-industry partners. References Arlt, W. G. (2006). China’s outbound tourism. Routledge. Bull, A. (2012). Obama orders streamlining of foreign tourist visas. Retrieved 07.02.12, from. . Canadian Tourism Commission (CTC). (2007). Consumer research in China. Ottawa, Canada: Canadian Tourism Organization, Retrieved from. . Carroll, B., & Alexandris, K. (1997). Perceptions of constraints and strength of motivation relationship to recreational sport participation in Greece. Journal of Leisure Research, 29(3), 279e299. Chick, G., & Dong, E. (2003). Possibility of refining the hierarchical model of leisure constraints through cross-cultural research. In Northeaster recreation research symposium, Newtown Square, PA. Conference.

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Chengting Lai recently graduated from the Master of International Hospitality and Tourism Management program of the School of Hotel, Restaurant, and Tourism Management at the University of South Carolina in Columbia.

Xiang (Robert) Li, Ph.D. (corresponding author), is an associate professor at the University of South Carolina in the School of Hotel, Restaurant, and Tourism Management. He is also the school’s Ph.D. program coordinator. Robert’s research mainly focuses on destination marketing and tourist behavior, with special emphasis on international destination branding, customer loyalty, and tourism in Asia. Robert is the author or co-author of over 80 scientific publications, and recipient of nearly $700,000 research funding. His research findings have appeared in numerous top-tier tourism, business, leisure, and hospitality journals. He currently serves on the Global Insights Advisory Council for Brand USA.

Rich Harrill, Ph.D., Research Professor and Acting Director of the University of South Carolina’s School of Hotel, Restaurant, & Tourism Management. Dr. Harrill earned his Ph.D. in Parks, Recreation, and Tourism Management and his master’s degree in City and Regional Planning from Clemson University. He holds a B.A. in Political Science from the College of Charleston. He has published his research in three of urban planning’s top journals: the Journal of American Planning Association, Journal of Planning Education and Research and Journal of Planning Literature.