Motivations and Constraints of Chinese Backpacking “Donkey Friends”: Mediating Effect of Negotiation Strategies

by Yingying Li

A Thesis presented to University of Guelph

In partial fulfilment of requirements for the degree of Master of Science in Tourism and Hospitality

Guelph, Ontario, Canada © Yingying Li, July, 2020 ABSTRACT

MOTIVATIONS AND CONSTRAINTS OF CHINESE BACKPACKING “DONKEY FRIENDS”: MEDIATING EFFECT OF NEGOTIATION STRATEGIES

Yingying Li Advisor:

University of Guelph Marion Joppe

The Chinese backpacking market is rapidly growing with backpackers affectionately referred to as “Donkey friends”. However, few studies so far have explored the motivations, constraints and negotiation strategies employed by domestic Chinese backpackers in a holistic way. The constraint-effect-mitigation model (Hubbard & Mannell, 2001) was employed in a Chinese backpacking tourism context to determine a) the motivations and constraints that have the most significant impact on travel intentions, and b) how negotiation strategies are navigated when making travel decisions. 502 valid questionnaires were collected and the results confirm that motivations have a positive influence on backpacking intention and negotiation strategies while intrapersonal constraints have a negative influence on backpacking intention. The more interpersonal constraints backpackers have, the more likely they look for negotiation strategies. Negotiation strategies partially mediate the relationship between motivation and backpacking intention. For Chinese backpackers, relaxation and escape, destination experience, self exploration and improvement and social interaction are all motivations that drive them to go backpacking.Even though an interpersonal constraint is the most frequent one they have, an intrapersonal constraint has a stronger effect on travel intention for Chinese backpackers. Practical implications are given to help improve the Chinese backpacking tourism market.

Keywords: Chinese backpackers, travel motivation, travel constraint, negotiation strategies, the constraint-effects-mitigation model iii

ACKNOWLEDGEMENTS

First of all, I would like to express my sincere gratitude to my advisor Prof. Marion Joppe for the support of my master study and research. Her guidance helped me throughout the research and thesis progress. She gave me professional comments on my paper and also helped me with my grammar, which is a huge help for a non-native English speaker.

Besides my advisor, I would like to thank the rest of my thesis committee: Prof. Statia Elliot, Prof. Erna van Duren, Prof. WooMi Jo and Prof. William Murray, for their encouragement, insightful comments and helpful suggestions.

My sincere thanks also goes to Dr.Ye Shen, for helping me with my data analysis process. I would not have been able to make good progress with my data analysis without her help.

Last but not least, I would like to thank my family: my parents Lianhui Li and Lixian Cai, my boyfriend Corey Knight and my friends that I did not mention explicitly, for all their love and support.

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TABLE OF CONTENTS

ABSTRACT ...... ii ACKNOWLEDGEMENTS...... iii TABLE OF CONTENTS ...... iv List of Figures ...... vii CHAPTER 1. INTRODUCTION…………………………………………………………..…….1

1.1. Backpacking History and Backpacking in China ...... 1 1.2. Research Gaps and Study Objectives ...... 3 CHAPTER 2. LITERATURE REVIEW...... 6 2.1. The Development of Backpacking Studies ...... 6 2.2. Chinese “Donkey Friends” ...... 9 2.3. Motivation Studies...... 11 2.3.1. Motivation Theories ...... 11 2.3.2. Chinese Backpackers’ Motivations ...... 13

2.4. Constraints Studies ...... 17 2.5. Negotiation Studies ...... 21 2.5.1. Negotiation Theories ...... 21

2.5.2. Constraint, Motivation and Negotiation ...... 24

CHAPTER 3. METHODOLOGY ...... 29 3.1. Study population...... 29 3.2. Sample size ...... 29 3.3. Pre-testing Procedure ...... 30 3.4. Pilot Tests...... 30 3.5. Measurement Scales ...... 32 3.6. Data Analysis ...... 34 CHAPTER 4. RESULTS...... 35 4.1. Profile of the sample ...... 35 4.2. Description of Means...... 37 4.3. Model Testing ...... 43 4.3.1. Factor Analysis ...... 43 4.3.2. Path Analysis ...... 51

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CHAPTER 5. DISCUSSION...... 59 5.1. Chinese Backpackers: Motivations and Constraints ...... 59 5.2. The CEM model in Chinese Backpacking Context...... 63 CHAPTER 6. IMPLICATIONS………………………………………………………………...66

6.1. Theoretical Implications ...... 66 6.2. Practical Implications ...... 68 CHAPTER 7. LIMITATIONS AND FUTURE STUDIES ...... 71 CHAPTER 8. CONCLUSION ...... 74 REFERENCES ...... 76 APPENDICES ...... 83

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List of Tables Table 1. Broad Profile of Terms Related to Backpackers ...... 7 Table 2. Descriptions of Backpackers ...... 8 Table 3. Four Dimensions of Motivations ...... 16 Table 4. Chinese Tourists' Constraint Studies in the Last Decaded ...... 19 Table 5. Different Dimensions of Negotiation Strategies ...... 23 Table 6. Profilie of Respondents ...... 36 Table 7. Travel Preferences of Chinese backpackers ...... 37 Table 8. Mean and Standard Deviation of Motivation Items ...... 39 Table 9. Analysis of Variance (ANOVA) for Self Improvement and Exploration ...... 40 Table 10. Analysis of Variance (ANOVA) for Destination Experience...... 40 Table 11. Mean and Standard Deviation of Constraint Items...... 41 Table 12. Gender Difference for Constraint...... 41 Table 13. Analysis of Variance (ANOVA) for Intrapersonal Constraint...... 41 Table 14. Mean and Standard Deviation of Negotiation Items...... 42 Table 15. Analysis of Variance (ANOVA) for Negotiation Strategies...... 43 Table 16. Results of Confirmatory Factor Analysis……………………………….…...…...... 44 Table 17. Exploratory Factor Analysis Results for Chinese Backpackers' Motivation..…...... 46 Table 18. Exploratory Factor Analysis Results for Chinese Backpackers' Constraint...... 47 Table 19. Exploratory Factor Analysis Results for Chinese Backpackers' Negotiation Strategies...... 48 Table 20. Confirmatory Factor Analysis for Measurement Model...... 50 Table 21. Results of Structural Model………………...... 51 Table 22.Correlation between Constructs……………...... 52 Table 23.Regression of Constraint and Travel Intention...... 53 Table 24.Regression of Constraint and Negotiation Strategies...... 54 Table 25. Correlations between Motivations, Constraints, Negotiation Strategies and Intention……………………………………………...... 54 Table 26. Standardized Coefficients for Path Analysis………...... 56

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Table 27. Mediation Effect of Negotiation Strategies………...... 57

List of Figures

Figure 1. Proposed Model ...... 28 Figure 2. Final Model ...... 58

CHAPTER 1. INTRODUCTION

1.1. Backpacking History and Backpacking in China

Backpacking tourism, semantically, refers to a traveler carrying a backpack as they travel. In

China, there is a nickname for Chinese backpackers - “Donkey Friends’’. In mandarin, “donkey” is pronounced similarly to “travel”. Also, donkey are an important load carrier animal in China and evoke the image of backpackers who carry a big backpack when they travel. In Chinese culture, donkeys represent a hard working spirit which is also exhibited by backpackers because they are not afraid of the long travel, tough weather and other hardships on the way. Therefore, for Chinese people, “donkey friends” is a lovely nickname for “backpackers”. Loker-Murphy and Pearce (1995) believed that backpacking originated in the 17th and 18th century. During this period, people had two major motivations for travel: education (The Grand Tour) and work

(tramping). The Grand Tour is a period of foreign travel undertaken by rich people to finish their aesthetic education, and involved visiting historically significant locations such as Venice and

Rome. Unlike The Grand Tour, tramping for work was conducted by the working class. In the

18th century, more and more young people spent their time traveling and exploring, which Loker-

Murphy and Pearce (1995) called the Youth Movement. Nowadays, backpacking has become one of the most popular ways to travel, especially among young people (Zhang, Wu, & Li, 2007;

Ong & du Cros, 2012; Chen & Weiler, 2014; Zhang, Morrison, Tucker, & Wu, 2018).

In China, tourism is an important industry that began to develop with the implementation of the reform and opening up policy in 1978. This policy boosted the development of the economy because it moved the country from a planned economy toward a market oriented one, concurrently spurring the development of the domestic tourism market. Innovations in e-

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commerce such as mobile travel platforms and mobile payment also helped to expand the tourism industry in China (Li, 2019). The Golden Weeks and the One Child policy contributed to the development of the domestic market (Chen & Weiler, 2014). The Golden Weeks include two week-long holidays celebrating the National Day and the Chinese Spring Festival, which provides people the ability to travel further on their vacation. Due to the implementation of the

One Child policy, many young people in China grow up as an only child. They receive all the attention from their family but at the same time also feel more isolated from their peers compared to those who have siblings (Chen & Weiler, 2014). Therefore, young people are attracted to travel and the opportunity to forge friendships. According to Zhang (2018), in the first half of 2018, Chinese tourists visited domestic attractions over 2.8 billion times, up 11.4 percent year-on-year. The revenue generated by domestic tourism was 2.45 trillion yuan ($358 billion), a 12.5 percent increase from 2017. According to the Ministry of Culture and Tourism, there were 782 million domestic tourists trips during the 2019 National Day holiday, up 7.81 percent from 2018 (Lin, 2019).

Due to these phenomena, domestic backpacking tourism in China has been popular since the

1990s (Zhu, 2009). Previous studies have demonstrated that the vast majority of Chinese backpackers are mainly 18-35 years old (Zhang, et al., 2007; Ong & du Cros, 2012; Zhang, 2013;

Chen & Weiler, 2014; Zhang, et al., 2018). In Richard and Wilson’s study (2004), students are an extremely important portion of the backpackers market, which take 70% of their survey population. Among those students, more than 60% are aged between 20 and 25 . Those students constitute an important part of the future tourism market as they influence the travel trends including preference for hostels, buying habits etc. According to Hotel.com’s annual Chinese

International Travel Monitor (2018), for those born in the 1990s, who are between 19 and 28,

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their average daily travel spending reached $314, an increase of 80%. This generation has a huge impact in boosting the tourism economy in China, so their role cannot be ignored. Therefore, further investigating the phenomena will lead to important insights into a massive, emerging market.

1.2. Research Gaps and Study Objectives

There are three study gaps in Chinese backpacking tourism studies. First of all, Chinese researchers began focusing on backpacking tourism much later than Western researchers (Zhu,

Su, & Peng, 2013). Cohen (1972) divided tourists into institutionalized and non-institutionalized tourists: institutionalized tourists are dealt with in a routine way by the tourist system, such as travel agencies, travel companies and hotel chains. Non-institutionalized tourists include the explorers and drifters, who do not rely heavily on the tourist establishment. Backpackers have similar travel characteristics as drifters, who venture furthest away from the beaten path of their home country. Since Cohen (1972), Western researchers started to pay attention to backpacking studies. However, Chinese backpacking tourism did not begin until the early 21st century (Zhu,

Su, & Peng, 2013). At first, Chinese researchers introduced the conclusions of different backpacking studies produced by Western researchers to Chinese academia (Sheng, 2003; Lin,

2012). For instance, Sheng (2003) summarized Western backpackers’ travel behaviors: they travel longer than the institutionalized tourists, have a more flexible timetable, prefer doing adventurous activities and communicating with other tourists. At the end, she suggested that backpacking tourism in China is still in its infancy and needs more attention. Since different

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cultural backgrounds and society lead to different travel motivations and constraints, there is a need to increase focus on the particularities of the Chinese backpacking market.

Motivation studies help to understand what drives people to backpack, how to satisfy tourists’ needs and ensure the sustainable development of a backpacker tourist industry. However, in the studies of Chinese tourists’ travel motivations, backpackers have usually been ignored. Yet

Chinese backpackers are a group of young people (between 18 to 35 years old) and the vast majority of them are well educated (bachelor’s degree or above)(Zhang, et al., 2007; Ong & du

Cros, 2012; Zhang, 2013; Chen & Weiler, 2014; Zhang, et al., 2018), which could make their motivations different from other Chinese travelers groups. Besides, there is a need to explore what motivations influence Chinese backpackers significantly and how these are shaped by

Chinese culture and society.

Last but not least, this study explores Chinese backpackers’ constraints, the factors that limit tourists to go backpacking. If constraints are removed, the likelihood of going backpacking will increase. The Hierarchical Constraint Model proposed by Crawford and Godbey (1987) has been widely used in leisure studies. It divides travel constraints into intrapersonal, interpersonal and structural constraints. Even though constraints research was introduced in the 1980s, it was not applied in Chinese tourism studies until the 21st century. Constraints studies have mainly been used to explore the Chinese outbound tourism market (Sparks & Pan, 2009; Li, Zhang, Mao, &

Deng, 2011; Lai, Li, & Harrill, 2013; Zou & Petrick, 2016) while more focus should be put on the emerging Chinese domestic tourism market. Since backpackers are mainly young people who make up a large and continuously growing percentage of the Chinese tourism market, there is a need to understand their travel constraints.

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In summary, this study takes Chinese backpackers as the research object, aiming to measure their travel motivations, travel constraints and negotiation strategies in order to better understand this market segment. Study objectives include:

1. To identify the demographic characteristics and travel preferences of domestic Chinese backpackers

2. To explore their motivations and constraints, and document how they negotiate through constraints by using a constraint-effect-mitigation (CEM) model 3. To reveal how Chinese culture and society play a role in influencing their motivations and constraints 4. To help backpacking organizations and marketers to improve the Chinese domestic backpacking market

By studying motivations and constraints of Chinese backpackers, this study helps backpacking organizations and marketers to better target this potential segment. Sheng (2003) highlighted some problems that exist in this market. For instance, due to the lack of understanding of

Chinese backpackers, few travel agencies provide backpacking itineraries for this specific group, and ultimately their travel packages are often canceled because of not enough participants.

Meanwhile, backpackers have higher requirements as they want more freedom and flexibility in their schedule, which makes it difficult for travel agencies to generalize their travel needs in order to provide a service or a product that satisfies them. Last but not least, the domestic backpacking market is still growing rapidly. In 2015, the term “shuo zou jiu zou”, which means, a trip without a plan, went viral on the Internet. This term shows young people’s urgent need to get away from structure in their daily life by travelling. If backpackers’ motivations and constraints are studied, travel agencies and marketers will gain better insights into how to develop their products to address backpackers’ needs, and achieve sustainability in this market.

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CHAPTER 2. LITERATURE REVIEW

2.1. The Development of Backpacking Studies

In the early 1970s, a conceptual and historically focused foundation was laid in the literature, which was essential to guide subsequent research (Ateljeric & Doorne, 2004). Cohen (1972) proposed a typology of four tourist segments: the organized mass tourist, the individual mass tourist, the explorer and the drifter. He classified the first two types as institutionalized tourists while the last two were deemed non-institutionalized tourists. In the 1960s and 1970s, there was a sizable demographic of students who felt a large degree of stress and uncertainty from modern society and in response, decided to ‘take time out’ to have new experiences via travel. This group was identified as “drifters” by Cohen (1972), as they represent the archetypal backpackers.

Cohen (1972) described drifters as a group of travelers who venture furthest away from the beaten path and the accustomed way of life of their home country. They avoid any kind of connection with tourist establishments, tend to schedule the whole trip on their own, try to live like locals by sharing the same shelter, food and habits. Cohen (1972)described their travel characteristics as “novelty is at its highest, familiarity disappears almost completely (p. 168).”

Building on Cohen’s study (1972), Vogt (1976) used the term “wanderers” to describe tourists who have similar travel characteristics as backpackers, and to distinguish them from mass tourists. In his study, the primary motivation for wanderers is personal growth, which is achieved through the decision-making process in daily life, the exposure and stimulation from novel and diverse environments and transient yet intense interpersonal relationships. These two terms are recognized in backpacking studies because Cohen’s discussion (1972) contextualizes travelers’ behaviors based on the society and change while Vogt (1976) explored the internal dynamics of

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backpackers’ culture and consumer psychology (Ateljevic & Doorne, 2004; Lin, 2012).

Contemporary backpackers embrace the ideology of drifting and imitate the style or form of travel characteristics of the drifters, though the mode or type of experience they pursue varies widely, these two terms could be seen as the archetypes of “backpackers”. (Cohen, 2003).

During the 1980s, backpacking studies transited their early conceptualizations of long term travelers to their conceptualization as a coherent “market niche”, exploring the internal complexities of subculture in terms of motivation, behaviour and socio-psychological characteristics (Ateljevic & Doorne, 2004). Their redefinition captured the main characteristics of backpackers such as “young budget travelers” (Loker-Murphy & Pearce, 1995), “minimalist”

(Hampton, 1998), “lifestyle traveller” (Cohen, 2011) and so on. Hampton (1998) recognized that backpackers have significant economic effects, which indicates the shift of the term from a de- marketing to a marketing approach. Table 1 summarizes some terms related to backpackers and

Table 2 summarizes descriptions of backpackers found in previous studies.

Table 1. Broad Profile of Terms Related to Backpackers Authors Terminology Description They immerse themselves in the local culture. They do not have a fixed travel itinerary. They display characteristics of "individualism”, “hedonism” and Cohen (1972) Drifters “anarchism”, and the process of drifting is often accompanied by drug culture. They are driven by cultural encounter.

Vogt The majority are youthful adventurers on a tight budget. They are motivated by Wanderers (1976) experiences offering personal growth. They travel to novel and diverse environments with independent and adventurous spirits.

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Table 2. Broad Profile of Backpackers

Authors Terminology Descriptions They are different from "drifters" described by Cohen (1972). Most of them are Long Term educated middle class people. They have flexible timetables and most expect to Riley Budget rejoin the workforce in their countries. They travel with a budget, and therefore (1988) Travelers tend to visit developing countries to allow themselves to stay as long as possible. They are a wealthy society’s modification of drifters. 5 keys characteristics: a preference for budget accommodation; an emphasis on Loker-Murphy meeting other people; an independently organized and flexible travel schedule; & Pearce Backpackers longer rather than brief holidays; and an emphasis on informal and participatory (1995) recreation activities.

Hampton Also described as “Minimalist”. They have a low budget for accommodation, Backpackers (1998) transport and dining facilities compared to mass tourists. Even so, they still bring benefits to local economy.

Maoz & Young tourists who tend to gather in ghettos or enclaves: places where large Bekerman Backpackers numbers congregate to experience home comforts and the company of tourists of (2011) similar interests.

However, there are some problems associated with defining exactly what or who backpacker is , because backpackers are not easy to be defined economically or demographically (Nash,

Thyne & Davies, 2006). Cederholm (2004) suggested that describing backpackers based on the structural and material conditions such as mode of transportation, accommodation and equipment like clothing and backpacks, would be more convenient. There are some main characteristics that backpackers widely shared, such as having a flexible timetable. Among all the descriptions,

Pearce’s (1995) five criteria is widely used in backpacking studies (Sheng, 2003; Nash, et al.,2006; Pearce, 2007; Luo, et al., 2015). However, describing backpackers does not mean one has to meet all the descriptions of the five criteria, Pearce (2007) mentioned that the first criteria

“a preference for budget accommodation” is a necessary condition while the four are strong indicators of the backpacker phenomenon.

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Even though many studies described backpackers based on tangible attributes (travel behaviors) , some argued that backpackers should be described by their intangible attributes, such as their motivations for backpacking. Richard and Wilson (2004) indicated the problem with describing backpacking based on travel behaviors is that this does not uncover how the participants see themselves. The relationship between previous definitions and the actual experience of travelers themselves could be clear if backpackers define their own travel styles. In the Chinese backpacking context, Zhang, et al. (2018) argued that defining them by their travel behaviors can be difficult because behavioral norms are not homogeneous, such as budget and length of trip. Moreover, the line between Chinese backpackers and other kinds of independent travellers is growing increasingly blurred. Therefore, Zhang et al. (2018) urged that type -related attributes should be the core factors in defining them. Based on the literature, it is still unclear whether we should define backpackers based on the tangible attributes or intangible attributes. It is hard to find a description that fits with all types of backpackers. Since the research object of this study is Chinese backpackers, it is necessary to clearly elucidate their uniqueness and thus arrive at a more comprehensive description.

2.2 Chinese “Donkey Friends”

Cohen (2003) argued that backpackers from non-Western countries are worth studying due to each country’s unique culture and social background. According to previous studies, Chinese backpackers differ from their Western counterparts, as follows:

(1) Chinese “donkey friends” travel for shorter time periods (Luo, et al., 2015; Zhang, et al.,

2017). The majority stay between 2 to 7 days while Western backpackers tend to stay more than

2 weeks on average (Luo, et al., 2015).

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(2) Chinese “donkey friends” are highly dependent on the Internet (Ong & du Cros, 2012; Luo, et al., 2015; Zhang, et al., 2017; Cai, Cohen & Tribe, 2019). Their primary information sources are travel websites, where they exchange travel advice with other travellers (Ong & du Cros,

2012) and look for travel companions (Cai, et al., 2019). Western backpackers are more likely to obtain travel information from travel guidebooks compared to Chinese donkey friends.

(3) Chinese “donkey friends” are more likely to organize themselves into groups, which is partly due to the influence of traditional culture (Chen & Weiler, 2014; Luo, et al., 2015; Ong & du Cros 2012; Cai, et al., 2019). During travel, they nominate one individual to be a team leader, who becomes responsible for the group’s safety and making important decisions (Luo, et al.,

2015). They also build online communities, which help them to find travel companions (Cai, et al., 2019). Because they travel in groups, they are more likely to interact with their own group members instead of interacting with local people (Chen & Weiler, 2014; Luo, et al., 2015).

(4) Chinese “donkey friends” have stricter gender roles (Ong & du Cros, 2012; Chen & Weiler,

2014). Influenced by Confucian thought, which suggests that women play a more supportive role than men, female backpackers are not encouraged to do physically strenuous work (Ong & du

Cros, 2012). Instead, they are expected to do the cooking when traveling in groups (Chen &

Weiler, 2014).

(5) Chinese “donkey friends” have a more flexible budget than their Western counterparts

(Chen & Weiler, 2014; Cai et al., 2019). For example, they are more likely to rent a car when they travel, while Western backpackers are more likely to take public transport (Chen & Weiler,

2014).

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Since Chinese “donkey friends” exhibit significantly different travel behaviours than their

Western counterparts, it is imperative to find a description that better reflects the tendencies of this group. It is not accurate enough to describe Chinese backpackers by using the description of

Western backpackers nor limiting the description to their tangible attributes. Therefore, this study aims to find a description more geared toward Chinese backpackers by combining their tangible attributes (travel characteristics) and intangible attributes (travel motivations). The tangible attributes of Chinese were explored in previous literature such as they prefer travelling with a budget and in groups. To better complete this description with their intangibles attributes, their travel motivations should be explored.

2.3. Motivation Studies

2.3.1. Motivation Theories

Motivation studies began to emerge in the 1960s. Murray (1964) believed that “a motive is an internal factor that arouses, directs and integrates a person’s behavior (p. 7).” Building on

Murray, Iso-Ahola (1982) stated that some stimulus factors, which might potentially provide the sense of satisfaction, are able to motivate a sequence of behaviors. In tourism studies, travel motivations are used to answer the question: “what makes tourists travel?” Dann (1981) proposed a definition for travel motivations as “a meaningful state-of -mind which adequately disposes an actor or a group of actors to travel, and which is subsequently interpretable by others as a valid explanation for such a decision (p. 205).” Therefore, travel motivations can be described as the forces that initiate, direct, and sustain travel behaviour.

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By studying travel motivations, travel needs and tourists’ behaviours can be better understood, providing necessary information for travel operators to reach potential tourists (Xie & Ritchie,

2019). Lin (2012) pointed out that the push-pull theory, the seeking-escaping model and the travel career ladder are frequently employed in travel motivation studies.

Dann (1977) defined “pull” factors as those that attract tourists to the destination and whose value is seen to reside in the object of travel. “Push” factors are factors which predispose people to travel, such as getting away from their daily life or having new experiences. By combining push and pull factors, researchers can explain why tourists want to travel to a specific destination.

However, Dann (1977) argued that push factors are more important than pull factors for several reasons. First, the choice of destination is the consequence of one’s travel needs. When one has the desire to travel, he would choose a specific travel destination. In other words, push factors are the antecedent of pull factors. Second, to answer the question “what make tourists travel?”, one’s inner needs need to be explored which are more important than the features of a particular destination. Therefore, building on the previous studies, this study will pay more attention to push factors than the pull factors that drive Chinese backpackers to go backpacking.

Iso-Ahola (1982) pointed out that seeking rewards and escaping the everyday environment are two determinants of travel motivations. When one is seeking intrapersonal rewards, he might look for self-enhancement, relaxation or an opportunity to learn about a new culture. When he is seeking interpersonal rewards, he might seek social interaction in travel. Escaping the intrapersonal environment means escaping from personal troubles and difficulties, while escaping from the interpersonal environment refers to escaping the troubles or stress from the relationship with family, friends, co-workers etc. The seeking-escaping model focuses on one’s psychological needs.

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The travel career ladder (TCL) was developed by Pearce (1988), based on Maslow’s analysis of needs, and is commonly used in measuring backpackers’ travel motivations (Loker-

Murphy, 1997; Paris & Teye, 2010). There are five factors in the TCL: relaxation/bodily need, stimulation, relationship, self-esteem and development and fulfilment. They are captured in a ladder shaped model. Among them, the relaxation/bodily need is the foundation of the ladder, which means they are the most basic factor in the model. Fulfilment is at the top as the highest level of one’s needs. The higher steps will come into play only after the needs from the lower steps are achieved or satisfied. Also, when one accumulates more travel experiences, a person will advance up the hierarchy. Loker-Murphy (1997) used TCL to segment Australian backpackers by dividing them into four clusters: social/excitement seeker; escapers/relaxers; achievers and self developers. Paris and Teye (2010) argued that the hierarchical structure in

TCL might lead to some issues because different people have different motivations, and motivations can change over time. Therefore, they use the travel career pattern (TCP) to examine different dimensions of motivations of backpackers. TCP agrees with the five basic factors of

TCL but it de-emphasizes its hierarchical focus. Paris and Teye (2010) concluded that cultural knowledge and relaxation form the core of backpackers’ motivations, and other factors, such as independence and personal growth, are dynamic throughout backpackers’ motivations.

2.3.2 Chinese Backpackers’ Motivations

Core motivations of non-Chinese backpackers include seeking social interaction, relaxation, self-growth and self-development, and excitement. (Loker-Murphy, 1997; Uriely, Yonay, &

Simchai, 2002; Pearce & Foster, 2007; Paris & Teye, 2010; Cohen, 2011). While research on

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Western backpackers is well developed, studies about Chinese backpackers’ motivations are in their infancy. These studies tend to apply qualitative methods more frequently than quantitative methods, which demonstrates the lack of sophistication currently employed in this domain and is a reflection of the research stage.

Chen and Weiler (2014) analyzed Chinese backpackers’ travel motivations to visit Tibet by looking at the tourism cyberspace forums. Self-actualization and destination experiences are the two main travel motivations. Social interaction, escape and relaxation do not show up in high frequency in this study. Chen, et al. (2013) took a mixed method approach to segment Chinese backpackers by motivations. Web-based content analysis and in-depth interview were employed before sending out the questionnaires. Both 416 usable questionnaires were collected from

International Youth Hostels in Qinghai, Tibet and Hainan. There are four main travel motivations in this study: social interaction, self-actualization, destination experience, and escape and relaxation. We can thus conclude that there are several distinct motivations for Chinese backpackers: escape and relaxation, destination experiences, self- exploration and improvement, and social interaction (Table 3). These motivations are about fulfilling needs or escaping from some certain environments (Chen &Weiler, 2014; Chen, et al., 2013), which conform to the descriptions of Iso-Ahola’s model (1982). Therefore, this study will employ the seeking- escaping model to explore Chinese backpackers’ travel motivations and which push factors motivate them to travel.

These four main motivations reflect some of the Chinese traditional values. Escape and relaxation illustrate the idea of “Zhongyong”, which means the “Doctrine of the Mean”.

“Zhongyong” represents the idea of balance and moderation. In Fu, Cai and Lehto (2015)’s study on the effects of Confucian ideas on Chinese tourists, they explained the idea of “Zhongyong” in

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Chinese tourists’ motivation: they do not want to be overwhelmed by work and obligations, and traveling helps them balance their energy and recover physically and mentally. Besides

“Zhongyong”, the value of harmony has been discussed in Chinese tourists’ studies (Fu, et al.,

2015; Cai, et al., 2019; Jiang, Scott, Tao & Ding, 2019). Harmony is an important concept in

Confucianism and Buddhism, referring not only to a harmonious interpersonal relationship, but also to a “human-nature” relationship. Chinese tourists regard a harmonious relationship with their co-workers, friends or family as very important. Therefore there are some related notions such as “quanzi” (social circle 圈子) and “guanxi” (relationship 关系) that are frequently discussed by Chinese tourists. During their travel, they hope to strengthen a relationship with their companions. When they have disagreements with each other, they tend to acquiesce more easily to avoid conflicts and maintain a relationship (Cai, et al., 2019). Besides maintaining a firm relationship with other people, Chinese also emphasize their relationship with nature.

Taoism and Buddhism encourage “the unity of human and nature”, believing nature shows all essence of life such as birth and death. In these philosophies, going back to nature means going back to the simplicity of life. This allows them to derive moral and spiritual inspiration from

Mother Nature, therefore achieving a harmonious relationship between humans and nature (Fu, et al., 2015; Jiang, et al., 2019). Therefore, by influencing the four dimensions of motivation, this study aims to find which one influences Chinese backpackers the most and how this is shaped in Chinese society and culture. Thus, this study proposes:

H1: There is a positive relationship between motivations and travel intentions.

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Table 3. Four Dimensions of Motivations (Paris & Teye, 2010; Chen, et al., 2013; Jensen & Hjalager, 2018)

Cronbach Alpha and Factord Dimensions Descriptions Items Covered in Previous Literature Loadings in Previous Literature

Paris & Teye, 2010: 0.792 To relax physically 0.879 To be in a calm atmosphere 0.743 To relax mentally 0.731 To avoid hustle 0.646

Escaping daily routine of Chen, et al., 2013: 0.627 Escape and life and work to obtain Escaping daily routine life and work 0.819 relaxation physical and psychological Relaxing both physically and psychologically 0.776 release Getting some fresh air because of confusion about the future 0.676 Jensen & Hjalager, 2018: 0.712 Getting away from daily routine 0.828 Getting away from everyday duties 0.822 Temporarily not worrying about future 0.661 Paris & Teye, 2010: 0.672 To explore other cultures 0.769 To increase my knowledge 0.764 To interact with local people 0.618 Chen, et al., 2013: 0.791 0.862 Involvement in or exposure Communicating with local people Destination to the cultures, landscape Knowing and understanding the local culture, Experience and lifestyle in the places history and society 0.801 vistied Experiencing local way of life 0.789 Jensen & Hjalager, 2018: 0.817 Exploring other culture 0.786 Learning about other culture 0.764 Interacting with the local people 0.754 Getting authentic and genuine experiences 0.547 Paris & Teye, 2010: 0.841 Re-evaluate and discover To use my physical abilities/ skills 0.689 Self one's personal image by exploration understanding themselves To contribute something to the places I visit 0.641 and and improving their To challenge my abilities 0.638 improvement characters, skills or capacities. Chen, et al., 2013: 0.739 Knowing and understanding myself 0.733

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Improving personal skills 0.718 Testing myself 0.635 Developing personal capacity 0.611 Jensen & Hjalager, 2018: 0.832 Challenging myself mentally 0.786 Understanding more about friends myself 0.781 Gaining a new perspective on my own life 0.667 Paris & Teye, 2010: 0.841 To build friendships with others 0.577 To gain a sense of belongings 0.571 To develop close friendships 0.475 To associate with other travelers 0.473 Chen, et al., 2013: 0.672 Meeting other people and In search of the other half of my life (a relationship/ Social 0.716 establishing a relationship heterosexual friends) Interaction and identity Making me different from the others 0.671 Communicating with and learning from other 0.637 backpackers Making new friends 0.556 Jensen & Hjalager, 2018: 0.710 Creating joy and value for local people 0.618 Creating new friendships 0.550

2.4. Constraints Studies

Beginning in the 1980s, leisure researchers started to study constraint theories and how constraints limit leisure participation. Constraints to leisure behaviour can be defined as the factors that limit people from taking part in, enjoying or getting satisfaction from leisure activities (Jackson, Crawford, & Godbey, 1993). Lacking interest or knowing nothing about it are not conceptualized as constraints as one must have the desire to enact the behaviour (Wu &

Pearce, 2018). The leisure constraints model proposed by Crawford and Godbey (1987), further elaborated by Crawford, Jackson and Godbey (1991), is commonly employed in constraints research. This model explains that there are three dimensions of constraints that inhibit people from taking part in leisure activities: intrapersonal; interpersonal and structural constraints.

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Intrapersonal constraints are psychological factors that prevent individuals from realizing their desires, such as anxiety and worries. Interpersonal constraints are external factors from a relationship which limit one’s ability to engage in some behaviours, such as stress from friends or from family, or the lack of travel companions. Structural constraints are the intervening factors between leisure preference and participation which include economic resources, time availability, weather and other external factors.

Table 4 summarizes some studies in the last decade discussing about Chinese tourists’ constraints, highlighting that their main focus is on outbound tourists. Crawford and Godbey’s

(1987) constraint model has been frequently used in these constraint studies.

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Table 4. Chinese Tourists’ Constraints Studies in the Last Decade

Author (year) Method (Sample size) Research Aim Constraints-related findings

To develop a comprehensive theoretical framework in understanding Chinese Structural (far distance, few travel agencies, difficulties Telephone interview mainlanders revisit to in getting document) , interpersonal (no travel Huang & Hsu, 2009 (501) HongKong by understanding companions) and disinterest are three underlying travel motivation, perceived factors. constraints and past travel experience

To explore constraints experienced by Chinese Structural constraint, cultural constraint, information Li, Zhang, Mao & outbound tourists and to Questionnaire(457) constraint and knowledge constraint are the main four Deng, 2011 segment the market based on constraint. Structural constraint is the most dominant. major constraints they encountered

Intrapersonal (have been there before; want to travel to To examine Chinese outbound other countries; too old to travel) and structural Lai, Li, & Harrill, Questionnaire (1600) tourists' perceived constraints constraints (time and distance constraint; security 2013 to visiting the United States concerns; money concerns and difficulty in getting visas) were of particular importance for respondents.

To examine the effects of Structural constraints (lack of places/facilities; micro (i.e., motivation, crowding; lack of time) were found to be the most constraint) and macro (i.e., Liu & Walker, 2015 Questionnaire (316) important barrier to Chinese people’s LTPA urbanization) factors on participation, which is similar to some Western studies' Chinese people's leisure time findings. physical activity.

Eight kinds of constraints for older Chinese female to To identify older Chinese go travel:”limited knowledge of tourism”, “health and female’s perception of safety concerns”, “culture shock”, “lack of travel Gao & Kerstetter,2016 Interview (16) constraints to pleasure travel pattern”, “low quality service facilities”, “limited and to document how they availability of information” “negative reputation of tour negotiate constraints guide” and “few employer paid vacation”.

To understand the travel Domestic nationalist sentiment plays a key constraining Lin,Qiu Zhang, Gu Focus group and in constraints and travel role, followed by current political factors, cultural &Peng, 2017 depth interview(49) attractiveness in outbound distance, destination factor, personal constraint and Chinese tourists to Japan information communication and media influence.

In order, the constraints were financial and time issues, To analyze what may lack of travel companions, social responsibility Wu & Pearce, 2018 Questionnaire (515) constrain Chinese tourists to obligations, personal skills and safety concerns, and do gap time competing interests.

To explore travel constraints experienced by mainland Major constraints include the lack of information and Chinese international students In depth interview equipment, the perception of risks, parental disapproval Mei & Lantai, 2018 in Norway and reasons for (15) and scared of “losing face”. experiencing such constraint

and to understand how those constraints are managed

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Intrapersonal constraints are defined as “individual psychological states and attributes, which interact with leisure preferences rather than intervening between preferences and participation”

(Crawford & Godbey, 1987, p. 122). In other words, intrapersonal constraints are those individual psychological factors which prevent travelers from participating even though they would prefer to go. Some studies have put “disinterest” as one of the measurement items of intrapersonal constraint (Huang & Hsu, 2009; Lai, et al., 2013), but disinterest does not meet the description of “intrapersonal constraint” and its inclusion would influence the results of the studies.

Most research about constraints argued that structural constraints are the most difficult to negotiate (Crawford, et al., 1991; Lai, et al., 2013; Liu & Walker, 2015; Smith & Smith, 2017) as they include the lack of money (Fredman & Heberlein , 2005; Nyaupane & Andereck, 2007;

Liu & Walker, 2015; Smith & Smith, 2017; Wu & Pearce, 2018), long distances (Fredman &

Heberlein, 2005; Lai, et al., 2013), difficulty in applying for visas (Lai, et al., 2013), and the lack of transportation (Gage & Thapa, 2012).

Interestingly, interpersonal constraints are particularly significant in China since this is a collectivist country, which is influenced heavily by family values. Generally for a Chinese person, the decision-making process includes consultation with their family, whereas in Western countries, the emphasis on individualism means they are less influenced by family relationships.

For example, Wu and Pearce (2018) explored Chinese tourists’ constraints in taking gap time, and found that social responsibility is the third constraint after the financial and time constraints.

Specifically, in traditional Chinese families, a young person is responsible for taking care of their elderly parents. A frequent visit is required when parents are old. Therefore, it is hard for a young Chinese person to take gap time for too long. Besides, doing so can be seen as uncommon

２０

or a waste of time by their peers, therefore gap time takers would feel the stress from their family and society. However, despite Chinese culture emphasizing interpersonal relationships, some studies concluded that interpersonal constraints have a negligible influence on travel intention

(Lai, et al., 2013; Boo, Carruthers & Busser, 2014; Xie & Ritchie, 2019). Due to the unique cultural background, interpersonal constraints should be considered in Chinese backpacking studies. Since constraints are those factors preventing tourists from going backpacking, this study proposes:

H2a: There is a negative relationship between intrapersonal constraints and travel intention.

H2b: There is a negative relationship between interpersonal constraints and travel intention.

H2c: There is a negative relationship between structural constraints and travel intention.

2.5. Negotiation Studies

2.5.1. Negotiation Theories

Many studies have addressed the relationship between motivations and constraints. They attempted to observe how these two constructs influence the participation in a leisure activity by using quantitative methods (Gage & Thapa, 2011; Zheng, Zhang, Qian, Jurowski, Zhang, & Yan,

2016). These studies assumed that constraints are not negotiable and the effects of motivations and constraints on the participation in a leisure activity cannot be altered. However, Jackson, et al. (1993) suggested that this is not so. People may find a way to modify their behaviours so they can take part in activities. Through the use of negotiation strategies, a balance between motivations and constraints can be established. Constraint negotiation refers to the strategies that avoid or reduce the negative influence of constraints (Mannell & Kleiber, 1997). Two types of negotiation strategies were introduced (Jackson, et al., 1993; Jackson & Rucks, 1995): cognitive

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and behavioural strategies. A cognitive strategy is the means of reducing an individual’s psychological discomfort by ignoring the perceived constraints in order to minimize the dissonance between attitude and behaviour (Jackson, et al., 1993). Jackson and Rucks (1995) examined how junior high school students deal with the leisure constraints they meet. The cognitive strategy they adopted included trying to ignore constraints or being more positive and having fun. Adopting a behavioural strategy means individuals make modifications in other leisure or non-leisure activities in order to participate in a preferred activity (Lyu, 2012). For example, an older Chinese female might participate in “donkey travel” or square dancing, which provides them an opportunity to meet new friends and identify potential travel companions when they lack travel partners (Gao & Kerstetter, 2016). Table 5 concludes different negotiation strategies that were employed in constraint-negotiation studies, and it shows that behavioural strategies are more frequently studied than cognitive strategies. In terms of behavioural strategies, time management, interpersonal coordination and finance management are three main dimensions tested.

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Table 5. Different Dimensions of Negotiation Strategies

Cronbach Alpha and Factord Dimensions Items Covered in Previous Literature Loadings in Previous Literature Cognitive Strategies Xie & Ritchie, 2019: 0.600 I tried to persist until I overcome obstacles (e.g time, money) in traveling 0.843 I tried to push myself harder when I experienced some obstacles in traveling 0.667 Time Management Hubbard & Mannell, 2001 0.790 I try to teach my kids to be more responsible and help with things N/A I cut short the activity session N/A I get up earlier or stay up later to increase fitness and recreation time N/A Boo, et al., 2014 0.748 I tried to oset time aside to participate in the event 0.764 I tried to adjust my work schedule to participate in the event 0.740 I thought of an easy way to access the event site to save time and to avoid crowds 0.620 Interpersonal Coordination Hubbard & Mannell, 2001 0.700 I try to find people with similar interests N/A I participate in activities with people of the same gender N/A I try to find people to do activities with N/A 0.920 (Loading in the structural White, 2008 model) Try to find people with similar interests 0.660 Ask my family to share the chores 0.546 Bring other people to make me feel safer 0.522 Organize events with my own group 0.532 Boo, et al., 2014 0.730 I tried to find people who could participate in the event with me 0.889 I tried to find people who had similar interests in the event 0.903 I tried to participate in the event with people of the same gender 0.500 Improve Finances Hubbard & Mannell, 2001 0.610 I try to budget my money N/A I have just learned to live within my means N/A I improvise with the equipment and/or clothes I have N/A 0.670 (Loading in the structural White, 2008 model) Try to budget my money 0.732 Set aside money to use for recreation 0.894 Boo, et al., 2014 0.766 I tried to budget my money 0.823 I thought of how I could save money before participating in the event 0.779 I tried not to spend too much money for local events 0.672

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Based on previous studies, negotiation strategies helped tourists minimize the effects of travel constraints to increase the possibility that they can travel. Therefore, this study proposes that:

H3: There is a positive relationship between the use of negotiation strategies and travel intention.

2.5.2. Constraint, Motivation and Negotiation

In previous studies, motivations were widely applied to explain leisure travel intentions, but the role of motivations in the constraint negotiation process had been ignored (Hubbard & Mannell,

2001; Zheng, et al., 2016). Jackson et al. (1993) claimed that the degree and interaction of constraints and motivations together would influence the outcomes of the negotiation process.

Therefore, many studies have argued that motivations should be taken into account in constraint studies (Fredman & Heberrein, 2005; Boo, et al., 2014; Zheng, et al., 2016). White (2008) tested the relationship between motivation, constraint and negotiation and found that motivation has a positive effect on negotiation, which suggests that a great desire to do a recreational activity triggers the use of negotiation strategies. Xie and Ritchie (2019) also tested the relationship between motivations and negotiation of international student leisure travellers, and pointed out that the more travellers are motivated, the more frequently they would use negotiation strategies.

Since the role of motivation is rarely tested in constraint research.

Previous studies have also discussed how constraints influence the use of negotiation strategies

(Jackson & Rucks, 1995; Boo, et al., 2014; Xie & Ritchie, 2019). Jackson and Rucks (1995) found that the majority of students would choose behavioral strategies when they have constraints. Boo, et al. (2014) tested the relationship between constraints and the use of negotiation strategies of non-participants in a festival event, and concluded that structural

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constraints have a significant influence on negotiation strategies which indicates that constraints influence the use of negotiation strategies. However, Son, Mowen and Kerstetter (2008) studied senior adults’ constraints in doing physical leisure in a metropolitan park and found that constraints and negotiation work independently on participation, so there is no significant relationship between constraints and negotiation strategies. They suggested that it might be because some constraints are not negotiable and have been existed for a long time. All in all, the relationship between constraint and negotiation strategies still needs to be discussed, therefore this study proposes:

H4: There is a positive relationship between motivation and the use of negotiation strategies.

H5a: There is a positive relationship between intrapersonal constraints and the use of negotiation strategies.

H5b: There is a positive relationship between interpersonal constraints and the use of negotiation strategies.

H5c: There is a positive relationship between structural constraints and the use of negotiation strategies.

2.5.3. Mediation Effects of Negotiation

Hubbard and Mannell (2001) built four models to test the relationship between motivation, constraint and negotiation in order to see how these three constructs influence corporate employees’ participation in recreation activities. The four models were: independence model; negotiation-buffer model; constraint-effect-mitigation model; and perceived-constraint-reduction

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model. Of these four, the constraint-effect-mitigation model fit the best with the data. This model hypothesized that motivation influences leisure activities positively while constraint influences leisure activities negatively. Encountering constraints triggers the use of negotiation strategies, and the more negotiation strategies are used, the higher the participation level. Motivation has a positive impact on negotiation and influences participation indirectly. This model shows that meeting constraints directly triggers the use of negotiation strategies which mitigate the negative effects of constraints. Also the mitigation model identifies motivation as an important factor because people who are highly motivated are more likely to put efforts into negotiating and consequently have a higher level of participation.

The constraint-effects-mitigation model (Hubbard & Mannell, 2001) has been tested in different leisure studies. White (2008) applied this model to participation in outdoor recreation in

Arizona State Park. His study supports most of the hypotheses but the relationship between negotiation and participation was not significant. Son, et al. (2008) applied this model to middle- aged or older people’s participation in physically active leisure. They concluded that the relationship between motivation and participation was fully mediated by negotiation strategies but there is no mediation between constraint and negotiation strategies. The authors argued that possibly due to the age of the participants, some constraints are hard to solve by negotiation such as some physical limitations, therefore in their study, negotiation plays a role as facilitator. They suggested that the relationship between constraints and negotiation should be tested in future studies as their results could not be generalized. Xie and Ritchie (2019) applied the model to understand international student leisure travellers. They concluded that negotiation mediated the relationship between constraints and participation as well as between motivation and participation, which confirmed Hubbard and Mannell’s study (2001). Since the mediation effect

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of negotiation strategies differed in previous studies, this study would test the mediation effect in the Chinese backpacking context, and therefore proposes that:

H6: Negotiation strategies mediate the relationship between travel constraints and travel intention.

H7: Negotiation strategies mediate the relationship between travel motivations and travel intention.

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Figure 1. Proposed Model: Motivations, Constraints and Negotiation Strategies for Chinese backpackers

Motivation

H1 (+)

H4 (+)

H3 (+) Negotiation Intention

H5 (+)

Constraint H2 (-)

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CHAPTER 3. METHODOLOGY

3.1. Study population

The target population of this study is Chinese backpackers who backpacked in the past 12 months. During the survey, respondents were to recall their travel motivations, travel constraints and negotiation strategies, and whether they intend to go backpacking in the next one to two years. Since Chinese backpackers are still a new group of travelers whose travel characteristics are not fully identified, this study asked respondents to self identify as backpackers. Screening questions included “Are you 18 years old and above?”, “Do you see yourself as a backpacker

(e.g. travel on a budget, prefer staying in a hostel etc)?” and “Have you done backpacking in

China within the past 12 months?”. Undoubtedly, some backpackers do not stay in hostels or do not choose public transportation while they travel, and might therefore be excluded, but these screening questions aimed at including the majority of Chinese backpackers.

3.2. Sample size

Comrey and Lee (1992) suggested a sample size of 200 as fair, 300 as good, 500 as very good and 1000 as excellent for factor analysis. Mundfrom and Shaw (2005) backed up their arguments by studying the minimum size recommendations for conducting factor analysis. They suggested if the variable-to-factors ratio is 4, the minimum sample size should be at least 500 for a high level of communality. Since there are 59 variables and 13 factors in this study, which surpasses the variable-to-factors ratio of 4, the target sample size was 500. Therefore, 824 questionnaires were collected and 502 were kept as valid questionnaires, with 61% usable response rate. Other questionnaires were deleted because respondents did not answer all questions.

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3.3. Pre-testing Procedure

Since this study aimed to test the CEM model in a backpacking context, quantitative research was called for. To test the hypotheses, this study used an online panel to target Chinese domestic backpackers. Before the distribution of the survey, back translation was used to ensure the accuracy of the translation of measurement items. Four people were invited to help with this process: three were master students in English translation and one was a master student in hospitality and tourism management. The hospitality and tourism management student translated

English into Chinese, and the three others did the back translation from Chinese to English. By comparing their translations, some errors were fixed. A pre-test with 15 people was undertaken after the back translation process. Their age range was between 20 and 66, and their education background covered secondary, bachelor’s degree and master’s degree. Their working status included working part time, full time and being students. They were asked to complete the questionnaires to see if there are any unclear items which might cause confusion.

3.4. Pilot Tests

After the pretest, this study collected data through the Chinese online research company

Sojump, which has 2.6 million active users, covers people from different ages, areas, socioeconomic statuses, employment statuses education levels etc, and therefore helped to ensure the diversity of Chinese backpackers. First, three pilot tests were run to ensure the reliability and validity of the measurement items. Questionnaires were sent on Sojump by simple random sampling, and 50 people completed the questionnaire each time. Cronbach alpha of each construct was tested and correlation analysis was employed. Some items in motivation and negotiation strategies were added based on the results. In the first pilot test, the Cronbach alpha

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in negotiation strategies was 0.357 was under the acceptable cut off point 0.6 (Results shown in

Appendix 7, 8 and 9). Therefore, in order to increase the reliability, 10 more items were added in negotiation strategies in the second pilot test, and instead of putting all the measurement items together as “behavioral strategies”, this study divided them into three dimensions : “time management”, “interpersonal coordination” and “money management” . The 10 newly added measurement items included : “I adjust my schedule to go backpacking” ,“I reorganize my schedule” , “I plan ahead and save time for backpacking”, “I try to make plan to better balance my life”, “I try to find people who could go backpacking with me”, “I try to find friends to go backpacking with me”, “ try to persuade people to go backpacking with me”, “I think of how I could save money before going backpacking”, “I try not to spend too much money when going backpacking”, and “I find a way to earn some money before going backpacking”. The newly items were drawn from previous studies testing constraint-effect mitigation model (Jackson &

Rucks, 1995; Hubbard & Mannell, 2001; White, 2008; Boo, et al., 2014). The results negotiation strategies were improved after adding items, with the Cronbach’s alpha 0.646. (Results shown in

Appendix 12). In the second pilot test (results shown in appendix 10, 11 and 12), the Cronbach alpha of motivation was 0.591, which was below the cut off point of 0.6. Therefore the study deleted some items including “To get more fresh air because of confusion about the future”, “To be liberated from social norms”, “To achieve balance in life”, “To seek other half of my life (a relationship/ a partner)” and “To make me different from others” to increase the reliability. 8 new items were added in motivation including “To relax and take things easy”, “To be liberated from daily routine, seek for time for my own”, “Relieve stress and tension”, “Get a break from everyday job”, “To learn something new/ increase knowledge”, “To accomplish/ achieve something”, “To fulfill an ambition” and “To build friendship with others” , to make each

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dimension sound stronger. In the third pilot test, the Cronbach alpha of motivation, constraint and negotiation strategies were 0.851, 0.875 and 0.789, respectively (shown in Appendix 13,14 and 15). Exploratory factor analysis (EFA) was conducted to justify the changes by testing the reliability and validity. For motivations, 13 measurement items were contained in the EFA and explained 62% of the variance (Appendix 16). EFA divided motivations into self growth

(α=0.785), culture learning (α=0.712), self development (α=0.782) and destination experience

(α=0.482). EFA of constraint divided items into three categories including intrapersonal

(α=0.824), interpersonal (α=0.718), and structural constraints (α=0.743), explaining 60% of the variance (Appendix 17). EFA of negotiation strategies in the third pilot test divided measurement items into interpersonal coordination (α=0.634), trip preparedness (α=0.640), cognitive strategies

(α=0.691), and time management (α=0.529), explaining 62% of the variance (Appendix 18).

Therefore, the overall results of the third pilot test reached the criteria, allowing for the launch of the full study.

3.5. Measurement Scales

The questionnaire was divided into two parts. The first part was about the basic personal profile of Chinese backpackers which includes their gender, birth year, educational background, employment status, personal monthly income (RMB), and their frequency of going backpacking.

The second part tested the four constructs: motivations, constraints, negotiation strategies and their travel intentions.

The motivations for backpacking were measured by 25 items assessing the importance of desired motivations (See appendix 1). Respondents rated each item on a five-point Likert-type scale (1=Strongly Disagree, 5=Strongly Agree). The list of items were adapted from previous

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research (Murphy, 1997; Pearce, 2007; Paris & Teye, 2010; Chen, et al., 2013; Xie & Ritchie,

2019). Those studies all discussed the motivations of backpackers, and similarly to those studies, this study divided motivations into 4 main parts: social interaction, destination experiences, self- improvement and relaxation.

To measure constraints, respondents rated their degree of agreement that certain constraints would prevent them from backpacking by using a five-point scale (1=Strongly Disagree,

5=Strongly Agree). Due to the absence of studies discussing Chinese backpackers’ constraints, this study adapted measurement items from other constraint studies about Chinese gap time takers and Chinese people’s leisure activities (Liu & Walker, 2015; Wu & Pearce, 2018). Even though they are not Chinese backpackers, they are constrained by a similar culture and social background. Their constraints are sorted into intrapersonal, interpersonal and structural constraints. 13 items measuring backpackers’ constraints were proposed (See appendix 2).

To measure negotiation strategies, respondents were asked to rate their degree of agreement with nine negotiation strategies to start, continue or increase participation in backpacking on a five-point scale (1=Strongly Disagree, 5=Strongly Agree). 17 measurement items of negotiation strategies were developed from previous studies testing CEM model (Jackson & Rucks, 1995;

Hubbard & Mannell, 2001; White, 2008; Boo, et al., 2014). These authors divided negotiation strategies into four dimensions: cognitive strategies, time negotiation, coordination negotiation and finance negotiation. This study tested these negotiation strategies to determine which one has the most significant influence on backpackers (See appendix 3).

The dependent variable of intention to participate in backpacking was measured by 4 items which were modified from Lyu (2012). Each item was measured on a five-point scale from 1

(Strongly Disagree) to 5 (Strongly Agree)(See appendix 4).

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3.6. Data Analysis

502 valid questionnaires were collected for data analysis process. First of all, a frequency analysis was conducted in SPSS 25.0 to test respondents’ demographic profiles and travel preferences. Another frequency analysis for constructs (motivation, constraint and negotiation strategies) and each measurement item were tested, by comparing their means and standard deviation, to see which measurement items have stronger influence on Chinese backpackers. T test and ANOVA were tested in each construct, to see how gender, age, their length of stay, and travel frequencies influence their travel preferences, motivation, constraint and negotiation strategies, to reach a better understanding on this group of travelers. Next, a confirmatory factor analysis (CFA) was conducted to test the validity and reliability of the model with dimensions from previous literature. However, the results of the CFA were not ideal and therefore an exploratory factor analysis (EFA) and another CFA were conducted to explore new dimensions in motivations, constraints and negotiation strategies. A structural equation modeling (SEM) was also conducted to explore the relationship between dimensions. Since the measurement items in

SEM could not fully represent the constructs, this study also conducted a multiple regression analysis and a path analysis to get an overall view of the model.

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CHAPTER 4. RESULTS

4.1. Profile of the sample

Table 6 presents the demographic characteristics of the respondents. Of the 502 respondents,

297 (59.2%) were male and 200 (39.8%) were female. The rest (1%) did not indicate their gender. The vast majority (89.3%) of the respondents were born between 1980 and 1999, or are between 21 and 40 years old. Half (52.4%) are between 21 and 30 years old. Respondents are well educated with 408 (81.3%) having a bachelor’s degree and 8.8% a master’s degree or higher.

In terms of employment status, the majority (75.3%) are employed full time and 15.7 % are students. As a result, the monthly incomes are relatively high: 40.3% of the respondents receive more than 7500 RMB ($1,500) per month, with a further 18.3% receiving a monthly salary in the range of 6001-7500 RMB ($1,200-$1,500). For reference, the median income in China was

$1530 in 2015 (Wen, 2018).

In terms of travel behaviors and travel preferences, nearly half (48.8%) of the respondents stay for eight days or less when they go backpacking, while 39.4% go for 9-14 days. 62.7 % of them go backpacking 2 to 3 times in the past 12 months, who are seen as repeated backpackers in

Jensen and Hjalager’s study (2019). There are 17.7% of them are first time backpackers and 19.7% of them are serial backpackers. These Chinese backpackers enjoy experiencing the local culture as much as possible (Mean=4.45, SD=0.616), engage in outdoor activities such as trekking and camping (Mean=4.28, SD=0.629), prefer to stay in a hostel (Mean=4.08, SD=0.833), travel with a flexible timetable (Mean=4.11, SD=0.843), have a tight budget in traveling (Mean=3.76,

SD=0.869) and use travel websites as the source of information (Mean=3.83, SD=0.917).

Surprisingly, they do not agree that they prefer to go backpacking in groups (Mean=2.80,

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SD=1.124), which is at variance with previous studies (Chen & Weiler, 2014; Luo, et al., 2015;

Ong & du Cros , 2012; Cai, et al., 2019). The travel preferences of Chinese backpackers are shown in Table 7 below.

Table 6. Profile of Respondents (N=502）

Variable Category Frequency Percentage

Sex Male 297 59.2% Female 200 39.8% Did not indicate 5 1% Birth Year Before 1980 28 5.6% 1980-1989 185 36.9% 1990-1999 263 52.4% 2000 and later 26 5.2% Education Level Secondary and below 17 3.4% Technical/Vocational school 33 6.6% Bachelor's degree 408 81.3% Master's degree and above 44 8.8% Employment Status Student 79 15.7% Employed full time 378 75.3% Employed part time 33 6.6% Temporarily unemployed/looking for work 11 2.2% Retire 1 0.2% Monthly Income (RMB) <1500 27 5.4% 1500-3000 46 9.2% 3001-4500 47 9.4% 4501-6000 88 17.5% 6001-7500 92 18.3% >7500 193 40.3% Choose not to respond 9 1.5% Length of Stay 8 days or less 243 48.8% 9 to 14 days 198 39.4% 15 to 21 days 38 7.6% 22 days and above 21 4.2% Times to Backpack in Past 12 Months 1 time 89 17.7% 2-3 times 315 62.7% Above 3 times 99 19.7%

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Table 7. Travel Preferences of Chinese backpackers (N=502)

Travel Preferences Mean SD When I go backpacking, I travel under a tight budget 3.76 0.87 When I go backpacking, I travel with a flexible timetable. 4.11 0.84 When I go backpacking, I prefer staying in a hostel. 4.08 0.83 When I go backpacking, I want to experience the local culture as much 4.45 0.61 as possible When I go backpacking, I look for travel information from travel 3.83 0.92 websites rather than reading travel guidebooks When I go backpacking, I prefer traveling in groups 2.80 1.12 When I go backpacking, I prefer doing some outdoor activities such as 4.28 0.63 hiking, trekking and camping

4.2. Description of Means

The means of the measurement items in motivations, constraint and negotiation strategies were explored. In motivations, respondents agreed that they are driven to do backpacking by these four dimensions of motivations: escape and relaxation (Mean=4.42, SD=0.28), destination experience (Mean=4.34, SD=0.29), self exploration and improvement (Mean=4.21, SD=0.39) and social interaction (Mean=4.10, SD=0.47). By comparing the means and standard deviation, escape and relaxation is the most common motivation for Chinese backpackers to go travel

(Table 8).

T-test and one way ANOVA were run to see how gender, age , the period of time that they travel and their frequencies in backpacking influence their travel motivation. The results indicate that there is no significant effect of gender and age on different dimensions of motivation

(p>0.05). However, the ANOVA results indicate that those who travel for 22 days or longer have

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the highest interest in going backpacking for self improvement reasons (Mean=4.43, SD=0.29), while the lowest group is those who travel for 8 days or less (Mean=4.17,SD=0.41, p. <0.05), a statistically significant variance between the different lengths of stay. It means that the longer backpackers travel, the more likely they are to be driven by the motivation of self exploration and improvement. Cohen (2011) has called for a distinct categorization of lifestyle travelers, who backpack as a way of life, and he argued that there is a difference between short term and long term backpackers. In this study, long term backpackers are more interested in the motivation of self improvement and exploration than short term backpackers, which is consistent with Cohen’s study (2011) (Table 9).

Previous studies discussed that backpackers’ motivations could change over time (Loker-

Murphy, 1997; Jensen & Hjalager, 2019), therefore this study also exams the motivations among first time, repeated (travel 2-3 times) and serial backpackers (over 3 times). The ANOVA test

(Table 10) shows that serial backpackers (Mean=4.38, SD=0.25) are more interested in destination experience than first time backpackers (Mean=4.23, SD=0.34) and repeated backpackers (Mean=0.35, SD=0.28), which indicates that the more Chinese backpackers go backpacking, the more they would be interested in learning the local culture and be immersed themselves in the local way of life, and it also meets the description of “lifestyle backpackers” that Cohen (2011) discussed.

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Table 8. Mean and Standard Deviation of Motivation Items

Motivations Mean SD Relaxation and Escape (Mean=4.42, SD=0.28) 1. To escape daily routine and pressure of life 4.43 0.55 2. To relax both physically and psychologically 4.56 0.58 3. To relax and take things easy 4.51 0.57 4. To be liberated from daily routine, seek time for my own 4.27 0.69 5. Relieve stress and tension 4.37 0.59 6. Get a break from everyday job 4.40 0.61 Destination Experience (Mean=4.34, SD=0.29) 1. To interact with local people 4.02 0.64 2. To study the local culture, history and society 4.55 0.59 3. To experience the local way of life 4.25 0.69 4. To seek new and unforgettable experience 4.21 0.72 5. To enjoy local natural landscape 4.58 0.54 6. To enjoy local cultural landscape 4.36 0.67 7. To achieve harmony between human and nature 4.34 0.64 8. To learn something new/ increase knowledge 4.41 0.64 Self Improvement and Development (Mean=4.21, SD=0.39) 1. To know and understand myself 4.29 0.57 2. To improve personal skills 4.31 0.73 3. To develop personal capacity 4.07 0.75 4. To change my characters 4.01 0.81 5. To accomplish/ achieve something 4.21 0.79 6. To fulfil an ambition 4.35 0.69 Social Interaction (Mean=4.10, SD=0.47) 1. To make new friends 4.08 0.70 2. To develop a new friendship 3.93 0.78 3. To communicate with and learn from other backpackers 4.25 0.69 4. To share feelings and build up connections with family and friends 4.17 0.78 5. To build friendship with others 4.07 0.69

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Table 9 . Analysis of Variance (ANOVA) for Self Improvement and Exploration

22 days and Variable 8 days or less 9 to 14 days 15 to 21 days ANOVA above Self Mean SD Mean SD Mean SD Mean SD F(3.330) p Improvement 4.17 0.41 4.21 0.36 4.26 0.37 4.43 0.29 0.50 0.019* Note * p<0.05, ** p<0.01

Table 10. Analysis of Variance (ANOVA) for Destination Experience

Variable First Time Repeated Serial ANOVA Destination Mean SD Mean SD Mean SD F(7.704) p Experience 4.23 0.34 4.35 0.28 4.38 0.25 0.639 0.001** Note *p<0.05, **p<0.01

The means and standard deviations of travel constraint were also explored. The results suggest that Chinese backpackers are influenced by interpersonal constraint (Mean= 3.43, SD=0.700) and structural constraint (Mean= 3.25, SD=0.679). They are least affected by intrapersonal constraint, with a mean of 2.92 and a standard deviation of 0.843. Among these three constraints, interpersonal constraint has a stronger impact on Chinese backpackers’ travel intention, which shows that the constraint model does not emerge in a hierarchical order (Table 11).

T-test and one way ANOVA were run to test how gender, age and length of stay affect

Chinese backpackers’ travel constraints. T-test indicates that female backpackers generally encounter more constraints than their male counterparts (M=3.36, SD= 0.53, compared to M=

3.12, SD= 0.54) (Table 12). The ANOVA results show that people who were born between 1990 and 1999, specifically, aged between 21 and 30 years, have the highest chance to encounter intrapersonal constraint (Mean=0.30, SD=0.80). People who are born between 1980 and 1989, aged 31 to 40, have the lowest chance to encounter intrapersonal constraint (Mean=2.75,

SD=0.86) as detailed in Table 13.

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Table 11. Mean and Standard Deviation of Measurement Items of Constraint

Constraint Mean SD Intrapersonal (Mean= 2.92, SD=0.843) 1. I am not confident of doing backpacking 3.04 0.96 2. I am not confident in my skills to go backpacking (understanding maps, 2.50 1.02 communicate with strangers, etc) 3. I worry about my personal safety 3.18 1.08 4. I worry backpacking involves too many risks 2.95 1.04 Interpersonal (Mean= 3.43,SD= 0.700) 1. I do not have backpacking companions 3.34 0.96 2. People with whom I would go backpacking are not interested in going with me 3.56 0.99 3. My family/ friends do not support me going backpacking 3.02 1.15 4. It is difficult to coordinate holiday with my family/ friends 3.59 1.03 5. People with whom I would go backpacking are on different schedules 3.65 0.91 Structural (Mean=3.25, SD=0.679) 1. Backpacking costs too much money 2.88 0.99 2. School/ work keeps me too busy to go backpacking 3.46 1.09 3. The places I want to go backpacking are too far 3.40 1.07 4. The destinations are poorly developed and maintained 3.24 1.03

Table 12. Gender Difference for Constraint

Variable Male Female df T Mean SD Mean SD Constraint 495 -4.942** 3.12 0.54 3.36 0.53 Note *p<0.05, **p<0.01

Table 13.Analysis of Variance (ANOVA) for Intrapersonal Constraint

Variable Earlier than 1980 1980-1989 1990-1999 Later than 1999 ANOVA Mean SD Mean SD Mean SD Mean SD F(4.395) p Intrapersonal 2.84 0.88 2.75 0.86 3.03 0.80 3.00 0.90 3.06 0.005** Note * p<0.05, ** p<0.01

When it comes to negotiation strategies, Chinese backpackers tend to use, in descending order,

time management (Mean= 4.28, SD=0.39), cognitive strategies (Mean= 4.23, SD=0.39), money

management (Mean=4.03,SD= 0.46) and interpersonal coordination (Mean= 3.94, SD=0.60)

(Table 14). T test and ANOVA were run to test their use of negotiation strategies when it comes

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to different ages, gender and the length of stay. The ANOVA results indicated that age influences the use of time management and interpersonal coordination strategies (p≤ 0.05).

Backpackers over 40 years old are more likely to manage their time when they travel

(Mean=4.34, SD=0.35), while backpackers who are younger than 21 years are less likely to manage their time compared to other backpackers (Mean=4.15, SD=0.42). When it comes to the use of interpersonal coordination, backpackers between 31 to 40 years old show the highest interest in finding travel companions (Mean= 4.05, SD=0.58) while backpackers less than 21 years (Table 15).

Table 14. Mean and Standard Deviation of Measurement Items for Negotiation

Negotiation Strategies Mean SD Cognitive Strategies (Mean=4.23,SD=0.39) 1. I ignore problems resulting from going backpacking 3.99 0.57 2. I push myself harder when I encounter some obstacles while deciding to go backpacking 4.46 0.58 3. I persist until I overcome obstacles while deciding to go backpacking 4.10 0.70 4. I stay positive when I encounter obstacles while deciding to go backpacking 4.26 0.68 5. I accept the constraints I have and do my best to solve them 4.32 0.64 Time Management (Mean=4.28,SD=0.36) 1. I adjust my schedule to go backpacking 4.23 0.59 2. I reorganize my schedule 4.13 0.70 3. I plan ahead and save time for backpacking 4.34 0.67 4. I try to make plan to better balance my life 4.41 0.59 Interpersonal Coordination (Mean=3.94,SD=0.60) 1. I try to find people with similar interests 4.04 0.51 2. I try to find people who could go backpacking with me 3.95 0.64 3. I try to find friends to go backpacking with me 4.14 0.79 4. I try to persuade people to go backpacking with me 3.61 0.61 Money Management (Mean=4.03,SD=0.46) 1. I budget my money 4.40 0.60 2. I think of how I could save money before going backpacking 4.01 0.82 3. I try not to spend too much money when going backpacking 4.11 0.73 4. I find a way to earn some money before going backpacking 3.61 0.96

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Table 15. Analysis of Variance (ANOVA) for Negotiation Strategies

Variable Earlier than 1980 1980-1989 1990-1999 Later than 1999 ANOVA Time Mean SD Mean SD Mean SD Mean SD F p Management 4.34 0.35 4.32 0.32 4.25 0.38 4.15 0.42 2.593 0.052* Interpersonal 3.92 0.69 4.05 0.58 3.87 0.58 3.78 0.72 3.814 0.010** Coordination Note * p<0.05, ** p<0.01

4.3. Model Testing

4.3.1. Factor Analysis

A confirmatory factor analysis (CFA) was conducted to test the validity of the dimensions

mentioned in the literature review. The results did not indicate an adequate fit. The chi square/

degrees of freedom (X2/df) ratio was 1.525, which is less than 5. The root mean square error of

approximation (RMSEA) was 0.032 in this model, below the cut-off point of 0.08. The normed

fit index (NFI) and comparative fit index (CFI) were 0.642 and 0.836, respectively, which are

both lower than the acceptable point 0.9. Last but not least, the goodness of fit index (GFI) and

the adjusted goodness of fit index (AGFI) were lower than the cut-off point of 0.9, at 0.877 and

0.865 respectively, which did not indicate a good model fit.

The results of CFA did not confirm a strong validity of the measurement models. The

discriminate validity of motivation and negotiation failed to be achieved because the square root

of the AVE of both constructs are less than the absolute value of the correlations with another

factor. The convergent validity of constraint and negotiation failed to bea chieved because it is

below the cut off point 0.5 (Table 16).

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Table 16. Results of Confirmatory Factor Analysis

CR AVE MSV MaxR(H) Constraint Motivation Negotiation Constraint 0.706 0.470 0.004 0.910 0.686 Motivation 0.897 0.688 1.117 0.942 -0.062 0.830 Negotiation 0.741 0.424 1.117 0.784 0.067 1.057 0.651 Note: CR=Composite Reliability. AVE=Average Variance Extracted. MSV=Maximum Shared Variance.

Since conducting CFA did not show a good validity of the model, an exploratory factor analysis (EFA) was conducted on the 25 measurement items to explore new dimensional characteristics. Reliability analysis was conducted to test the measurement items of motivations.

The Cronbach alpha of the 25 measurement items is 0.747, which is higher than the acceptable point 0.6. The value of Kaiser-Meyer-Olkin is 0.779 (>0.7) with a chi-square of 1393.053

(p<0.05), indicating desirable sampling adequacy to run the EFA (Hair, Anderson, Tatham, &

Black., 1998). 13 measurement items were contained after using principal component analysis with varimax rotation, and the combined Eigenvalues explained 54.056% of the total variance

(Table 17).

Factor 1 is labeled as “social interaction”, which includes “To make new friends”, “To develop a new friendship” and “To build friendship with others”, indicating that participants’desire to get involved social activities and build connections with other people. This is one of the main motivations in previous backpacking study (e.g Loker-Murphy, 1997; Pearce,

2007; Paris & Teye, 2010; Chen, et al., 2013).

Factor 2 is labeled as “self improvement”, meaning that participants look forward to developing their skills and improving themselves during their backpacking trips. The second

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factor includs “ To improve personal skills”’ “ To develop personal capacity “ and “ To change my characters”. This motivation is also identified by previous backpacking research (e.g Loker-

Murphy, 1997; Pearce, 2007; Chen, et al., 2013; Chen & Weiler, 2014; Jensen & Hjalager, 2019).

Factor 3 is labeled as relaxation, meaning that participants relieve their stress by traveling in a new place and enjoying beautiful scenery. This is a frequently mentioned motivation in backpacking study (e.g. Loker-Murphy, 1997; Pearce, 2007; Paris & Teye, 2010; Chen, et al.,

2013). In this study, it includes measurement items “To enjoy local natural landscape”, “To enjoy local cultural landscape” and “ Relieve stress and tension”.

Factor 4, seeking new experience, indicates that participants look forward to gaining some new knowledge about the local destination and new experiences. This factor includes “To seek new and unforgettable experience” and “To learn something new/ increase knowledge”. This motivation has been discussed in previous backpacking studies (e.g. Peace, 2007; Paris & Teye,

2010; Xie & Ritchie, 2019; Jensen & Hjalager, 2019).

Factor 5 indicates participants look forward to escaping their daily routines and living in a local way of life during backpacking. Factor 5 shows some characteristic of drifters that Cohen (1978) proposed, such as immersing themselves in the local community during travel. In this study, factor 5 includes “To experience the local way of life” and “To be liberated from daily routine, seek time for my own”.

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Table 17. Exploratory factor analysis results for Chinese backpackers’ motivations

Factors Factor loadings Eigenvalue Social interaction (α=0.711) 2.491 To make new friends 0.789 To develop a new friendship 0.824 To build friendship with others 0.717 Self exploration and improvement(α=0.441) 1.304 To improve personal skills 0.622 To develop personal capacity 0.756 To change my characters 0.570 Relaxation (α=0.347) 1.184 To enjoy local natural landscape 0.594 To enjoy local cultural landscape 0.705 Relieve stress and tension 0.626 New experiences (α=0.301) 1.044 To seek new and unforgettable experience 0.738 To learn something new/ increase knowledge 0.711 New way of life (α=0.167) 1.004 To be liberated from daily routine, seek time for my own 0.694 To experience the local way of life 0.681 KMO=0.729, explained 54.056% of the total variance

EFA was also employed to test participants’ backpacking constraints. First of all, the reliability test was employed to test the measurement items of constraints, with the Cronbach alpha 0.790, higher than the cut off point 0.6, showing a good reliability to run EFA. The value of Kaiser-Meyer-Olkin is 0.822, with a chi-squared of 1661.424 (p<0.05), indicating desirable sampling adequacy to run the EFA (Hair et al., 1998). When running EFA, one item “I do not have backpacking companions” was deleted because of the low loadings. After deleting the item, the results divided measurement items into three categories of constraints: intrapersonal, interpersonal and structural constraints (Table 18), which meets the description of the constraint model that Crawford and Godbey (1987) proposed.

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Table 18. Exploratory factor analysis results for Chinese backpackers’ constraint

Factors Factor loadings Eigenvalue Intrapersonal constraint (α=0.841) 3.581 I am not confident of doing backpacking 0.801 I am not confident at my skills to go backpacking (understanding maps, communicate with strangers, etc) 0.748 I worry about my personal safety 0.817 I worry backpacking involves too many risks 0.845 Interpersonal constraint(α=0.684) 1.955 People with whom I would go backpacking are not interested in going with me 0.669 My family / friends do not support me to go backpacking 0.801 It is difficult to coordinate holidays with my family/ friends 0.561 People with whom I would go backpacking are on different schedules 0.757 Structural constraint (α=0.592) 1.145 Backpacking costs too much money 0.537 School/ works keeps me too busy to go backpacking 0.673 The places I want to go backpacking are too far 0.709 The destinations are poorly developed and maintained 0.616 KMO=0.814, explained 55.673% of the variance

EFA was also conducted to test the measurement items of negotiation strategies. The

Cronbach alpha of negotiation strategies is 0.657, which is higher than the cut off point 0.6. The value of Kaiser-Meyer-Olkin is 0.702, with a chi-squared of 885.824 (p<0.05). 5 measurement items were deleted because of the low loadings (below 0.4) when running EFA. 14 measurement items were contained after running EFA, which explained 55.747% of the total variance. After running EFA, measurement items of negotiation strategies were divided into five segments: interpersonal coordination, self challenge, determination and persistence, trip preparedness and money management (Table 19).

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Table 19. Exploratory factor analysis results for Chinese backpackers’ negotiation strategies

Factor Eigenval Factors loadings ue Interpersonal coordination ( α=0.682) 2.517 I try to find people who could go backpacking with me 0.748 I try to find friends to go backpacking with me 0.714 I try to persuade people to go backpacking with me 0.686 I try to find people with similar interests 0.702 Self challenge ( α=0.483) 1.674 I push myself haefer when I encounter some obstacles while deciding to go backpacking 0.629 I stay positive when I encounter obstacles while deciding to go backpacking 0.678 I accept constriants I have and do my best to solve them 0.583 Determination and persistence ( α=0.550) 1.365 I ignore problems resulting from going backpacking 0.780 I persist until I overcome obstacles while deciding to go backpacking 0.719 Trip preparedness ( α=0.385) 1.178 I budget my money 0.726 I adjust my schedule to go backpacking 0.625 I plan ahead and save time for backpacking 0.605 Money management( α=0.484) 1.071 I think of how I could save money before going backpacking 0.796 I try not to spend too much money when going backpacking 0.790 KMO=0.691, explained 55.747% of the variance

CFA was employed to identify the validity of the measuring items. Among dimensions of motivations, only the Cronbach alpha of social interaction (α=0.711) is higher than the cut off point 0.6. When running CFA, only measurement items in intrapersonal constraint (α=0.841) and interpersonal coordination (α=0.682) showed factor loadings higher than 0.5. Therefore, these three dimensions were run in CFA. One measurement items of negotiation strategies “I try to persuade people to go backpacking with me” was deleted due to the low loading in CFA, which was below 0.5. Both convergent and discriminate validity were tested in the CFA.

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Convergent validity of this study was achieved because all values of average variance explained

(AVE) were 0.5 or above (Hair, et al., 1998). According to Fornell and Larcker (1981), when the square root of the average variance explained (AVE) from a construct is larger than the correlations shared between the construct and other constructs in the model then they are discriminant from each other. In this study, all items met this criteria, and therefore discriminant validity is achieved. Composite reliability (CR) was chosen to evaluate reliability. Hair et al.

(1998) suggested CR as a popular alternative coefficient alpha, which is usually calculated as part of SEM and a CR value of 0.7 or higher suggests good reliability. In this study, the value of

CR ranges from 0.715 to 0.859, which shows good reliability (Table 20).

The CFA results indicate the research model is of adequate fit. According to Hu and Bentler

(1995), the rule that the chi square/degrees of freedom (X2/df) ratio should be less than 5

(X2/df=1.512; X2=83.155; df=55) was achieved in this model; this is used to justify the sensitivity of chi-square to a large sample size. The root mean square error of approximation

(RMSEA) is 0.039 in this model, below the cut-off point of 0.08. The normed fit index (NFI) and comparative fit index (CFI) are 0.936 and 0.977, respectively, indicating a good model fit since they are higher than 0.9 (Hair, et al., 1998). Last but not least, the goodness of fit index (GFI) and the adjusted goodness of fit index (AGFI) are higher than the cut-off point of 0.9, at 0.963 and 0.939 respectively, suggesting a good model fit.

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Table 20. Confirmatory factor analysis for measurement model

Factor Composite Items AVE Loadings reliability Social Interaction 0.5 0.715 To make new friends 0.76 To develop a new friendship 0.67 To build friendship with others 0.59 Intrapersonal Constraint 0.6 0.859 I am not confident of doing backpacking 0.75 I am not confident in my skills to go backpacking (such as 0.66 communicating with strangers) I worry about my personal safety 0.83 I worry backpacking involves too many risks 0.86 Interpersonal coordination 0.5 0.765 I try to find people with similar interests 0.68 I try to find people who could go backpacking with me 0.80 I try to find friends to go backpacking with me 0.68 Backpacking Intentions 0.5 0.733 I intend to go backpacking more often over the next 12 months 0.65 I am determined to go backpacking more often over the next 12 0.84 months I am likely to go backpacking more often over the next 12 0.57 months AVE: Average Variance Explained

Structural equation modeling (SEM) was used to test the hypotheses. The analysis indicates that the model shows a reasonably acceptable overall fit to the data: X2=88.261; df=56,

X2/df=1.576,GFI=0.962, AGFI=0.938, NFI=0.932, CFI=0.974, RMSEA=0.042.

Table 21 shows the standardized coefficients for the paths between latent factors. The data supports all the hypotheses expect for hypothesis 5: there is a positive relationship between constraint and negotiation strategies. The path was shown to be not significant (P>0.5).

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Table 21. Results of structural model Standardized Path t-value Results estimates H1: social interaction → intention 0.19 2.096* Supported H2: intrapersonal constraint → intention -0.23 -3.083** Supported H3: interpersonal coordination → intention 0.22 2.547** Supported H4: social interaction → interpersonal coordination 0.49 4.805*** Supported H5: intrapersonal constraint →interpersonal coordination -0.07 -1.131 Not Supported Note * p<0.05, ** p<0.01, *** p<0.001

Factor analysis initially supported all the hypotheses except hypothesis 5, however, one dimension of the construct could not fully represent the whole construct. Therefore, in SEM testing, this study focused mainly on one dimension of each construct: social interaction, intrapersonal constraint and interpersonal coordination because these three dimensions have the strongest loading in each construct, and they play an important role in influencing the results of the analytical model.

4.3.2. Path Analysis

Due to the results of EFA , only dimensions of constraints could be considered in the path analysis because all dimensions of constraint show a good reliability to run path analysis, with their Cronbach alpha close to or higher than 0.6 (Table 18). Therefore, in the first path analysis, constraints were divided into intrapersonal, interpersonal and structural constraint. Before path analysis, a correlation analysis was conducted to test the correlation among motivation, intrapersonal constraint, interpersonal constraint, structural constraint, negotiation strategies and

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travel intention. Pearson’s bivariate correlations (r) were tested to see the correlation between variables. Motivation (r=0.331, p<0.05), intrapersonal constraint (r=-0.213, p<0.05), structural constraint (r=-0.104, p<0.05) and negotiation strategies (r=0.299, p<0.05) correlate with travel intention. Interpersonal constraint (r=0.090, p<0.05) correlates with negotiation strategies.

Motivation (r=0.620, p<0.05) correlates with negotiation strategies (Table 22).

Table 22. Correlation between Constructs

Intrapersonal Interpersonal Structural Motivation Negotiation Intention Intrapersonal Pearson Correlation 1 .233** .382** -.127** -.086 -.213** Sig. (2-tailed) .000 .000 .004 .053 .000 N 502 502 502 502 502 502 Interpersonal Pearson Correlation .233** 1 .375** .053 .090* -.014 Sig.(2-tailed) .000 .000 .234 .043 .762 N 502 502 502 502 502 502 Structural Pearson Correlation .382** .375** 1 -.078 -.036 -.104* Sig. (2-tailed) .000 .000 .080 .419 .020 N 502 502 502 502 502 502 Motivataion Pearson Correlation -.127** .053 -.078 1 .620** .331** Sig. (2-tailed) .004 .234 .080 .000 .000 N 502 502 502 502 502 502 Negotiation Pearson Correlation -.086 .090* -.036 .620** 1 .299** Sig. (2-tailed) .053 .043 .419 .000 .000 N 502 502 502 502 502 502 Intention Pearson Correlation -.213** -.014 -.104* .331** .299** 1 Sig. (2-tailed) .000 .762 .020 .000 .000 N 502 502 502 502 502 502 Note * p<0.05, ** p<0.01

However, when testing the dimensions of constraint in path analysis, the results did not show a good model fit: X2/df=29.130, X2=174.782, DF=6, while the chi square/degrees of freedom (X2/df) ratio should be less than 5. The root mean square error of approximation

(RMSEA) is 0.237 in this model, higher the cut-off point of 0.08. The normed fit index (NFI) and comparative fit index (CFI) are 0.654 and 0.655 respectively, and they do not indicate a

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good model fit since they are below 0.9 (Hair, et al., 1998). The goodness of fit index (GFI) and the adjusted goodness of fit index (AGFI) are 0.891 and 0.619 respectively, suggesting a bad model fit since they are lower than the cut off point 0.9. Therefore, a multiple regression analysis was used to test how intrapersonal, interpersonal and structural constraint influence backpackers’ travel intention and their use of negotiation strategies.

In the first multiple regression analysis, the results showed the intrapersonal, interpersonal and structural constraints together explain 42% of the variance of travel intention. Only the beta values of intrapersonal constraint (β =-.0208, p<0.01) is significant. Thus, the hypothesis H2a that there is a negative relationship between intrapersonal constraint and travel intention is supported (Table 23).

Table 23. Regression of Constraint and Travel Intention (N=502)

Variable β T Sig. Intrapersonal -0.208 -4.374 .000 Interpersonal 0.051 1.084 .279 Structural -.0440 -.876 .381 R²=0.42, F=8.395

In order to examine hypothesis 5, another multiple regression analysis was conducted with variables of intrapersonal constraint, interpersonal constraint and structural constraint and negotiation strategies. The independent variable measured 22% (R²=0.22) of the negotiation strategies at a significant level of p<0.01. Table 24 shows that interpersonal constraint

(β=0.131,p<0.01) demonstrated significant β weight toward predicting negotiation strategies.

However, intrapersonal constraint (β=-0.099,p<0.05) has a very small influence in predicting negotiation strategies and there is no influence of structural constraint (β=-.048, p>0.05) on negotiation strategies.

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Table 24. Regression of Constraint and Negotiation Strategies

Variable β T Sig. Intrapersonal -0.099 -2.045 .041 Interpersonal 0.131 2.729 .007 Structural -.0480 -.943 .346 R²=0.42, F=8.395

Since testing constraint with dimensions in path analysis shows a bad model fit, this study decided to test the relationships between the construct without dimensions, to get an overall view of the model. Travel motivation (α=0.747), travel constraint (α=0.790), negotiation strategies

(α=0.657) and travel intention(α=0.623) were tested in the path analysis. Before conducting the path analysis, a correlation analysis was performed. Motivation (r=0.331, p<0.05), constraint (r=-

0.149, p<0.05) and negotiation strategies (r=0.299, p<0.05) correlate with travel intention.

Therefore hypotheses 1 to 3 were initially supported. To test hypotheses 4 and 5, another correlation analysis was performed. Motivation (r=0.620, p<0.05) is strongly correlated with the use of negotiation strategies. However, there is no correlation between constraint and the use of negotiation strategies, therefore hypothesis 5 is initially rejected.

Table 25. Correlation between motivations, constraints, negotiation strategies and intention

Motivation Constraint Negotiation Intention Motivation Pearson Correlation 1 -.066 .620** .331** Sig. (2-tailed) .141 .000 .000 N 502 502 502 502 Constraint Pearson Correlation -.066 1 -.012 -.149** Sig. (2-tailed) .141 .787 .001 N 502 502 502 502 Negotiation Pearson Correlation .620** -.012 1 .299** Sig. (2-tailed) .000 .787 .000 N 502 502 502 502 Intention Pearson Correlation .331** -.149** .299** 1

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Sig. (2-tailed) .000 .001 .000 N 502 502 502 502 Note **p<0.01

Next, a path analysis in AMOS 21.0 was performed. The average values for motivation, constraint and negotiation strategies were run to test the relationship. First of all, the data show a good model fit: According to Hu and Bentler (1995), the rule that the chi square/degrees of freedom (X2/df) ratio should be less than 5 (X2/df=2.178; X2=2.178; df=1) was achieved in this model. The root mean square error of approximation (RMSEA) is 0.048 in this model, below the cut-off point of 0.08. The normed fit index (NFI) and comparative fit index (CFI) are 0.993 and

0.996, respectively, indicating a good model fit since they are higher than 0.9 (Hair, et al., 1998).

Last but not least, the goodness of fit index (GFI) and the adjusted goodness of fit index (AGFI) are higher than the cut-off point of 0.9, at 0.998 and 0.978 respectively, suggesting a good model fit.

Table 26 shows the standardized coefficients for the paths between latent factors. The data supports all the hypotheses expect for hypothesis 5: there is a positive relationship between constraint and negotiation strategies. The path was not significant in this study (P>0.5).

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Table 26. Standardized Coefficients for Path Analysis Standardized Path t-value Results estimates H1: Motivation→Intention 0.224 4.233*** Supported H2: Constraint→Intention -0.132 -3.183** Supported H3: Negotiation→Intention 0.160 3.011** Supported H4: Motivation→Negotiation 0.621 17.758*** Supported H5: Constraint→Negotiation 0.029 0.824 Not Supported Note * p<0.05, ** p<0.01, *** p<0.001

Biased corrected (BC) bootstrap confidence intervals are used to examine the significance of mediation effects of negotiation strategies (Cheung & Lau, 2008; Lau & Cheung, 2012). The

Amos output shows that the estimated indirect effect from motivation to backpacking intentions through negotiation strategies is 0.099. The 95% BC confidence intervals for the indirect effect are between 0.015 to 0.169, with a p-value of 0.011 for the two-tailed significance test. The standardized direct effects estimate from motivation to intention is 0.224. The 95% BC confidence intervals for the direct effect are between 0.132 to 0.311, with a significant p-value of

0.01. Last but not least, the standardized total effects estimate from motivation to intention is

0.324, and the 95% BC confidence intervals are between 0.205 to 0.383, with a p-value of 0.030, which shows that negotiation strategies partially mediate the relationship between motivation and intention. As for the role of negotiation strategies in the relationship between constraint and backpacking intentions, the 95% BC confidence intervals for indirect effects are between -0.003 and 0.018, with a p-value of 0.193, which suggests that there is no mediation effect (Table 27).

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Table 27. Mediation effect of negotiation strategies

95% Confidence Interval Estimate p value BC Indirect Effect Motivation→Negotiation→Intention 0.099 0.011* 0.051-0.169 Direct Effect Motivation→Intention 0.224 0.010** 0.132-0.311 Total Effect Motivation→ Intention 0.324 0.030* 0.205-0.383 Note: * p<0.05, ** p<0.01, *** p<0.001, BC: Biased corrected percentile method

In summary, the results of the hypotheses support nearly all aspects of the model. In general, there is a negative relationship between constraint and travel intention. Specifically, there is a negative relationship between intrapersonal constraint and travel intention. When testing relationship without dimensions, there is no significant relationship between constraint and the use of negotiation strategies, however, there is a positive relationship between interpersonal constraint and the use of negotiation strategies. As for mediation effect, negotiation strategies partially mediate the relationship between motivations and backpacking intentions (Figure 2).

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Figure 2. Structural model of leisure constraint negotiation with standardized parameters estimate

Motivation

β=0.62(t=17.758)*** β=0.22(t=4.233)***

R2 =0.39

Negotiation R2 =0.14 β=0.16(t=3.011)* * Intention

β=0.03(t=0.824)

β=-0.13(t=-3.183)** Constraint

Note: Dotted line shows that relationship is not significant at 0.05 level *p<0.05, **p<0.01, ***p<0.001

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CHAPTER 5. DISCUSSION

5.1. Chinese Backpackers: Motivations and Constraints

The characteristics of Chinese backpackers can be summarized as follows: the vast majority of them are between the ages of 21 and 40 years, which is consistent with the previous studies

(Zhang, et al., 2007; Ong & du Cros, 2012; Zhang, 2013; Chen & Weiler, 2014; Zhang, et al.,

2018). They are well educated, since the majority of them having a bachelor’s degree or higher.

When they travel, they prefer to go for one to two weeks, which is shorter than for Western backpackers. Luo et al. (2015) explained that it might be the result of the short public holidays in

China, the intense and competitive work culture, and the family-oriented culture. Due to the large population, the competition for jobs is fierce so people have more fear of losing their jobs if they ask for a leave that is longer than two weeks. Chinese traditional culture expects people to spend time with their family, which in turn, prevents travel. Interestingly, this study found that

Chinese backpackers do not agree that they like to travel in groups (Mean=2.80, SD=1.12), which contradicts previous studies (Chen &Weiler, 2014; Luo, et al., 2015; Ong & du Cros,

2012). This might point to an emerging trend of more independent backpackers instead of group travelers. In summary, Chinese “donkey friends” could be described as a group of travelers who enjoy making new friends, engage in doing outdoor activities and/or look for meaningful experiences during travel, which are motivated by traditional Chinese value such as the value of harmony from Confucianism and Buddhism. Relaxation is the most significant motivation for

Chinese backpackers, confirming the results of previous backpacking studies (Paris & Teye,

2010; Alves, Abrantes, Antunes, Seabra & Herstein, 2016; Jensen & Hjalager, 2019).

Backpackers who travel more than 2 weeks are more likely to look for self growth and self

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development than those who travel for 1 to 2 weeks. And for serial backpackers, they value a destination experience more than other types. It illustrates that “lifestyle backpackers” in China value the destination and self improvement, and suggests a trend of pursuing educational meaning in the future backpacking market. The seventh Chinese International Monitor emphasizes “culture” and “educational experience” as two important factors for Chinese tourists in choosing their travel destination, especially for Millennials and the Gen-Z generation who seek adventures and uniqueness (Rapp & Zhang, 2018). “ Younger Chinese see their lifestyle as the way to express their personal brand, and travel is a hugely important part of the identity,” stated the CEO of Carat China in a recent report (Liang, 2018). It explains that the destination experience and self improvement are becoming important to younger generations in China. They look for opportunities to learn, grow and experience rather than shopping.

The most significant constraint for Chinese backpackers in my study is the interpersonal constraint, which is consistent with the previous study by Wu and Pearce (2018). Influenced by collectivist culture, Chinese backpackers feel more stressed from their interpersonal relationship compared to their Western counterparts (Wu & Pearce, 2018). Cai et al. (2019) stated that

Chinese cultural attributes such as guanxi (relationship 关系), keqi (courteous 客气) , conformity and respect for authority play a role in group dynamics to achieve a harmonious status. When going backpacking together, backpackers over practice keqi. When they have conflicts with each other, they prefer not to be open about their feelings, choosing rather to maintain the surface relationship between each other, which leads to confusion and a potential rift in the group.

Influenced by the traditional collectivist culture, it is harder for Chinese backpackers to develop a genuine relationship, which illustrates the strong influence of interpersonal constraint (Cai et al., 2019).

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When comparing gender difference in constraint, female backpackers encountered more constraints than male backpackers. Previous studies (Jordan & Gibson, 2005; Wilson & Little,

2005) discussed that social disapproval that women travelling alone still lingers in this contemporary society. Yang, Khoo-Lattimore, Arcodia (2018) discussed how solo Asian female travelers perceive risks, and they find out that gendered risks are one of the main risks that they encounter, which included street harassment, be sexually intimated or be mistaken as sex workers. Female backpackers would use cognitive strategies to negotiate with them. They are aware of the risks and constraints on their trip, yet they still want to be brave and go backpacking, because they think that the experience of looking for independence and freedom matter more to them. Besides sexual assault, women are still bound by the gender norms and power relations in the host society (Yang, et al., 2018). Obenour (2005) also mentioned that women female backpackers have a sense of autonomy and empowerment by backpacking, and this experience allow them to be liberated from their familial roles and social norms. Therefore, even female backpackers are more constrained than male backpackers, they still have a strong willing to go backpacking.

Intrapersonal constraints impact the different ages in diverse ways and each age group applies somewhat different negotiation strategies. Younger Chinese backpackers (18 to 30 years old) are more likely to encounter intrapersonal constraints than older backpackers (30 years old and above). The reason could be younger backpackers are students or workers who just graduated from school within the past 1 to 3 years, and they are still in the stage of exploring and developing themselves. Compared to the older backpackers, they still have more concerns about their skills and the ability to protect themselves. When it comes to negotiation strategies, older backpackers (above 30 years old) are more likely to manage their time and ask for travel

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companions. According to World Development Indicators (Halim & Rivera, 2020), in East Asia the average age at first marriage is 25 years, with men’s average age being 26 years and women’s 24 years. Therefore, it explains why backpackers older than 30 years have more need to schedule their time – they are required for more family responsibilities than younger backpackers. Chinese backpackers over 30 are similar to the “sandwich generation” in Western culture, who have stress from taking care of their parents and their children. In Confucius’s teaching, one should not go far away while one’s parents are still alive. Even though Confucian beliefs are not clearly understood by every Chinese, the philosophy still influences Chinese people deeply (Xu, Ding & Packer, 2008). Other than family responsibilities, it is also harder for them to ask for a leave from work because of the fierce competition in China (Luo, et al., 2015).

For example, in China there is a common expression describing the working culture: “996”. “996” means people work from 9 am to 9 pm, 6 days a week. This kind of work style is very common in some Chinese companies, especially in Internet companies. It shows that it is harder for backpackers who have a job to take some time out to go backpacking. In terms of interpersonal coordination, younger backpackers are less likely to ask for travel companions than older ones, which shows a trend of independent travel in backpacking. According to Ctrip (Liang, 2018), a popular Chinese travel website, as many as half of the bookings made through its site are for independent tours. Although group travel is still significant, young Chinese travelers are more attracted to the idea of looking for uniqueness and being independent when they travel.

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5.2. The CEM model in Chinese Backpacking Context

This study tested the constraint-effect-mitigation model in a Chinese backpackers context. The results partially support the hypotheses of this model (Hubbard & Mannell, 2001). First of all, the role of motivation has been recognized. There is a positive relationship between motivations and backpacking intention. Constraints are found to have a negative influence on backpacking intentions: the more constraints they have, the less they are willing to go backpacking, which is consistent with previous studies (Hubbard & Mannell, 2001; Son, et al., 2008; White, 2008; Xie

& Ritchie, 2019).To be specific, intrapersonal constraint has a stronger influence on travel intention than interpersonal constraint and structural constraint. This finding is consistent with

Xie and Ritchie (2019)’s study about international student leisure travellers. One possible explanation could be intrapersonal constraint is the most difficult one to solve. Backpackers need to conquer the insecurity and discomfort in their minds in order to go backpacking. Solving interpersonal and structural constraint, such as asking for a friend or schedule their timetable are easier than overcoming their psychological discomfort. Therefore, intrapersonal constraint has a stronger effect than other types of constraint in influencing travel intention. As well, there is a positive relationship between motivation and negotiation strategies, and negotiation strategies partially mediate the relationship between motivation and travel intention, which suggests that the more backpackers are motivated, the more likely that they use negotiation strategies to increase their interest to go backpacking.

However, in this study, the overall constraint does not have a direct effect on negotiation, and negotiation does not mediate the relationship between constraint and negotiation, which is contrary to the previous studies (Hubbard & Mannell, 2001; White, 2008; Xie & Ritchie, 2019).

Son, et al. (2008) studied senior adults’ constraints and negotiation strategies on doing physical

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leisure in a metropolitan park, and their results indicated that constraint and negotiation strategies work independently and with similar but opposite influences on participation. They explained this phenomenon by suggesting that the strategies and resources used by the respondents may play the role of facilitators instead of negotiators because the effects of negotiation are independent of participation. Hubbard and Mannell (2001) also pointed out that negotiation resources and strategies that were used to solve constraints could also be the general factors that can facilitate participation regardless if constraints are encountered or not. For example, in this study, backpackers do not have the money constraint (Mean=2.88, SD= 0.99), however they still agree that they would budget their money when they go backpacking (Mean=4.03, SD= 0.46), it explains that even constraint do not happen, they still tend to use negotiation strategies to increase their possibility to go backpacking. Therefore, in this study, negotiation strategies play a role of facilitators, working independently from constraint.

However, when testing the relationship between constraint and negotiation strategies with dimensions, only interpersonal constraint has a significant influence on backpackers’ use of negotiation strategies. The influence of intrapersonal constraint is very weak and there is no influence of structural constraint on the use of negotiation strategies. Tan, Yeh and Chen (2017) stated in their study :“which negotiation strategy is employed based on which constraints and negotiation strategies matter most to the leisure seekers, which in turn will depend on the nature of the activity (p.49)”,which means the nature of the activity decided which negotiation strategies would be used and therefore decide the relationship between constraint and negotiation strategies For example, in the SEM model (Table 20), there is no significant relationship between intrapersonal constraint and interpersonal coordination. However, regression analysis (Table 24) shows that there is a very small influence of intrapersonal constraint on the overall negotiation

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strategies, which means that the relationship between constraint and negotiation strategies are dynamic, and the relationship depends on what kinds of constraint backpackers encounter and negotiation strategies that they use.

This model suggests that backpacking marketers should focus on solving backpackers’ intrapersonal constraint, to help them conquer their psychological discomfort such as fear and being unconfident. By solving their intrapersonal constraint, backpackers would be more likely to increase their possibility to go backpacking and look for negotiation strategies. Even though interpersonal constraint is the most frequent constraint (Mean=3.43, SD=0.700), backpackers are more willing to look for negotiation strategies when having interpersonal constraint (Table 24), which makes interpersonal constraint less difficult to solve.

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CHAPTER 6. IMPLICATIONS

6.1. Theoretical Implications

First of all, this study focused on Chinese backpackers, which helped to fill a gap created by a lack of attention on non-western backpackers. Cohen (2003) mentioned that one of the shortcomings of the backpacking literature is that it tends to disregard the differences between backpackers, engendered by the specific problems and tensions experienced in their various home societies. Therefore, he suggested that research about backpacking studies should be extended to the emergent backpacking from non-Western countries, especially areas including

East Asia. Ateljevic and Doorne (2004) backed up this argument, commenting that there is a need for research to reveal even more heterogeneity. Meanwhile, the majority of motivational studies are from a limited Australasian context. Mao (2007) studied the national differences of

Israeli backpackers, and found that since Israeli youth have the compulsory military service experience, they are driven to go backpacking for relaxation purposes. They also tend to behave more permissively than others in terms of drug use and a disregard for local norms. He recognized that because of the different nationality, Israeli backpackers tended to behave differently than Western ones. Israeli backpackers are a uniquely well-studied group of non-

Western backpackers; however other nationalities should also be paid attention to. Newlands

(2004) studied backpackers in New Zealand and mentioned that there are increasing numbers of international visitors from Asia, especially from China. One proof of this is the industry’s response to new markets by updating Asian language translations on Auckland Central

Backpackers websites, which also illustrates there is an urgent need to understand and explore the Chinese market. Therefore, this study is one contribution to filling the gap that more attention

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should be paid to non-Western backpackers group. This is the first attempt to explore Chinese backpackers’ travel motivations, constraints and negotiation altogether. The four dimensions – relaxation and escape, destination experience, self improvement and development and social interaction – are all main ones driving the Chinese to go backpacking in this study. Among them, relaxation is the strongest. As for constraint, interpersonal and structural constraints have a stronger impact on Chinese backpackers than intrapersonal constraints. The impact of motivation and constraint differs based on the age group and the length of stay.

Moreover, this study has furthered the constraint-effect-mitigation model by applying it for the first time in a Chinese backpacking context. The study results suggest that this model fits well in this new context. First, the positive relationship between motivation and intention and the negative relationship between constraint and intention are confirmed. Therefore, backpacking organizations should not only focus on dealing with the negative relationship between constraint and backpacking intention, but also focus on the positive relationship between motivation and backpacking intention. Second, this study revealed a direct path from motivation to negotiation in the constraint negotiation process. To help backpackers address their constraints, backpacking organizations should boost backpackers’ motivation so that they are motivated to negotiate their constraint. Last but not least, the mediation role of negotiation strategies between motivation and travel intention is confirmed, which is consistent with previous studies about constraint- negotiation process. The original constraint effect mitigation model has been widened in the literature. This research is meaningful because it applies the theoretical model to another unique context, specifically, Chinese domestic backpacking, to fill the gap of literature. This fast growing market segment needs more attention.

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6.2. Practical Implications

Since CEM model shows a good data fit in this context, backpacking organizations and hostels could think about boosting backpackers’ motivations, solving their constraint and providing them negotiation strategies in order to increase their interests in going backpacking.

First of all, the vast majority (89.3%) of backpackers are Millennials, born between 1980 and

1990. It is important for backpacking organizations to understand the travel habits of this specific group. Millennial rely heavily on social media. Sampi Marketing report (2019) stated that social media is the main source of information for 70% of Chinese Millennials, and that they spend twice the amount of time watching online videos than Americans in a similar demographic. In this study, participants also agree that they look for travel information from websites rather than guidebooks (Mean=3.83, SD=0.92). To attract potential backpackers, especially millennial backpackers, organizations should consider promoting their brands through Chinese social media and Chinese websites, such as Weibo and Douyin, by posting short videos on these platforms.

Chinese Millennials are becoming more adventurous, seeking new experiences and uniqueness and seeing travel as an important part of their identity. Therefore, a short video of doing adventurous sports such as scuba diving, or a short vlog of attending a local festival on Douyin or Weibo, could be a good idea to attract millennial backpackers. Destinations should cooperate with key opinion leaders on Douyin or Weibo, especially with adventurous vloggers, by providing adventurous, exciting or educational contents to attract millennial backpackers.

Secondly, since destination experience (Mean=4.34, SD= 0.29) has a strong influence on millennial Chinese backpackers, backpacking destination should pay attention to the protection of their authentic culture. Chinese travelers look for the authenticity of the place when they travel.

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For a site, the integration of the physical buildings and spiritual meaning matter the most to them

(Xu, et al., 2008). It suggests that the protection of the environment and local historical culture is essential for the development of backpacking tourism. The measurement item “To achieve harmony between human and nature” (Mean= 4.34. SD=0.64) suggests that millennial Chinese backpackers value maintaining such a harmonious relationship. When they travel, they look forward to going to places with natural beauty and gaining a new perspective. For local destinations, they should develop ecotourism, protect native culture and natural landscape.

Localization and authenticity are two important factors for backpacking hostels. They could design the building by following the local historical architecture style or provide guests access to the local cultural heritages. They could also design a “theme hostel” to attract young Chinese backpackers, who look for uniqueness when they backpack.

Since this study shows that collectivist culture has a significant influence on millennial backpackers’ motivation and constraints, backpacking organizations should put an emphasis on providing a platform for backpackers to socialize. Some hostel owners could organize group activities such as going for local foods together, or going hiking to boost the connection between backpackers. Some hostels could even set up a small bar or a game room for young backpackers to socialize. For travel websites, they could provide some socialization activities for the backpacking community, such as helping them to find travel companions and organizing some group travel activities. In their study of backpacker employment in hostels, Cooper, O’Mahony and Erfurt (2004) found that backpackers generally stay longer and work harder in a hostel since they are working for a purpose. Some backpackers also regularly return every year. Therefore backpacker labour is of considerable importance because it helps to develop the local economy.

Chinese hostels and backpacker organizations could provide young backpackers short term job

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opportunities such as doing housekeeping and cleaning the environment. By doing this, backpackers could not only make friends with other travelers while working, but also build a connection with the local community and their workmates, which makes their trip even more meaningful. Since Chinese backpackers travel for a shorter period of time than their Western counterparts, short term projects are more important: for example, Sichuan province provides a panda protection project which lasts for 1 week. Backpackers could learn some knowledge about pandas,while working with other people to meet their needs for socializing.

Last but not least, female backpackers are more constrained than male ones, and those under

30 encounter more intrapersonal constraints than older backpackers. Therefore, addressing the constraints of young and female backpackers is important for the development of this tourism segment in China. Obenour (2005) discussed the travel constraints of female backpackers. He confirmed that they are limited by familial and interpersonal constraints, as they are expected to play the role of a good mother or a good wife in the society. In order to help them to solve their constraint, travel organizations could organize some “mother backpackers” events, helping female backpackers to take some time off from their family role and socialize with other backpackers who are mothers. Backpacking organizations could also organize them to do some challenging activities together, such as going trekking or snowboarding, helping them to reach a sense of achievement during their trip, and therefore boost their confidence in future travel.

Young backpackers encounter intrapersonal constraints because they are uncomfortable and worried about going backpacking, and therefore hostels could arrange a local guide for young backpackers when they do dangerous sports such as trekking and hiking, and provide them travel insurance service to ensure their safety, and therefore solve their intrapersonal constraint.

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CHAPTER 7. LIMITATIONS AND FUTURE STUDIES

There are some weaknesses in this study. First of all, the measurement items of motivations and negotiation strategies are mainly derived from Western studies, therefore they might not be able to fully represent Chinese backpackers. In-depth interviews or a focus group should be adopted to help researchers gain a deeper understanding of their motivations, constraints and negotiation strategies. By adopting qualitative methods, researchers might better understand how society and culture influence Chinese backpackers, and understand the cultural uniqueness of this group.

Secondly, due to the limitation of time, this study used an online panel to collect data, which might influence the results of the study to some degree. Previous studies (Loker-Murphy,

1997; Chen et al., 2013; Hecht & Martin, 2006) suggested that hostels could be a good location to collect data for backpacking studies because backpackers seek social connections and are more likely to stay in hostels. In this study, respondents agree that when they go backpacking, they prefer to stay in hostels (Mean=4.08 SD=0.83). Therefore, when collecting data offline, hostels could be a good location to select respondents.

Additionally, this study uses a path analysis because of the low loading of factors in confirmatory factor analysis. There are two reasons for this phenomenon: the four dimensions of motivations could be further divided into more dimensions and backpackers were seen as a homogeneous whole in this study. There are different categories of backpackers and their response would vary when answering the questionnaires, which leads to the low reliability in constructs, and therefore influences the results of the study. Therefore, in future studies,

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backpackers could be studied by length of travel, or divided into first time, repeat and serial backpackers (Jensen & Hjalager, 2019).

Also, when testing the model in SEM, this study only focused on one dimension of each construct with the strongest loading and therefore with the most significant influence on the model. When testing SEM model in path analysis, constructs were tested uni-dimensionally to obtain a holistic view on the SEM model in a Chinese backpacking context. However, there is a limitation in so far as this study did not look at all dimensions gathered at this time. In future research, different dimensions of motivations and negotiation strategies should be tested for a richer understanding, and for further exploration on the relationship between different dimensions.

Furthermore, relaxation and social interaction are strong motivators in this study while

Chen and Weiler (2014) found that these two dimension of motivation were rarely discussed by

Chinese backpackers. It could result from the difference in travel destinations since Chen and

Weiler (2014) studied Chinese backpackers in Tibet specifically. Tibet is one of the most remote regions in China and as such, the facilities there are under developed. Backpackers hike there, challenging their body limits instead of looking for relaxation. This demonstrates that where

Chinese backpackers go could influence their motivations. This study explores the general motivations but future studies could explore Chinese backpackers’ motivations and constraints when traveling to different places.

As well, this study recognizes the significance of collectivism in Chinese culture and its influence on Chinese backpackers. Therefore, group dynamics could be a good topic for researchers to explore further. While Western backpackers are studied as individuals, Chinese backpackers could be studied as a group. The relationship between team members, between the

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lead and the rest of the team members, and between genders could be studied from a traditional culture perspective (Cai, et al., 2019).

Finally, data collection of this study took place during the worst of pandemic influence in

China (February, 2020). In the pandemic, Chinese backpackers are not able to go travel, which might influence the results of this study more or less. For instance, because they are required to stay at home, participants would have a stronger need to escape their daily life and relieve their stress and boredom staying at home, which might influence the results of motivation. Their family would worry about them if they go travel during pandemic, therefore, they encounter stronger interpersonal constraint than usual.

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CHAPTER 8. CONCLUSION

First of all, after a pre-test and pilot tests, this study collected 502 valid questionnaires through an online panel and identified the demographic characteristics and travel preferences of Chinese domestic backpackers : they are a group of well-educated Chinese millennial (21-40 years old), who enjoy experiencing the host culture, prefer staying in a hostel, enjoy participating in outdoor activities and have a tight budget while traveling. However, when compared to Western backpackers, Chinese backpackers are more likely to travel in a shorter period of time (one to two weeks on average) while Western backpackers are more likely to travel more than two weeks. Chinese backpackers tend to look for travel information through travel websites than travel guidebooks, which demonstrates a higher reliance on the Internet.

In this study, the four dimensions of motivations: relaxation and escape, destination experience, self improvement and development and social interaction are all important to

Chinese backpackers. Among these motivations, long term backpackers who travel more than 2 weeks show stronger interest in self improvement and development than short term backpackers.

And serial backpackers are more interested in destination experience than first time backpackers and repeated backpackers. This suggests that Chinese backpacking studies could divided backpackers based on demographics or travel behaviors. Interpersonal constraint and structural constraint influence Chinese backpackers more than intrapersonal constraint, and it shows the strong influence of collectivist culture. Younger backpackers under 30 years old are influenced by intrapersonal constraint more than older backpackers. Female encounter more constraints than male backpackers. In terms of negotiation strategies, older backpackers are more likely to use time management and interpersonal coordination than younger backpackers, which reveals the influence of society and traditional culture on older Chinese backpackers. They feel stressed

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from their family and work responsibilities. The less frequent use of interpersonal coordination suggests that there is a future trend of independent travelers.

The CEM model was employed in a Chinese backpacking tourism context. The good model fits show that there is a positive relationship between motivation and intention, between negotiation and intention, and a negative relationship between constraint and intention.

Negotiation strategies partially influences the relationship between motivation and travel intention. It helps to further develop this model in constraint literature. It inspires backpacking organizations to not only focus on resolving backpackers’ travel constraints, but also to focus on boosting their motivations therefore backpackers are more motivated to solve their constraints and increase their interests in going backpacking.

Therefore, in order to develop backpacking tourism in China, backpacking organizations must make use of social media to promote their brands. In order to provide Chinese backpackers authentic travel experience, travel destinations should develop ecotourism, helping to protect the natural environment and cultural landscape. The localization and authenticity of hostels are also important in providing backpackers a meaningful travel experience. Besides protecting the authenticity of the local destination, providing backpackers a socializing platform could also help backpackers to strengthen their relationship with each other and satisfy their need for social interaction. All in all, Chinese backpackers show a future travel trend of looking for authenticity and being independent, which needs more attention from future studies because they reveal the tendency in the future tourism market.

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APPENDICES Appendix 1 Measurement Items for Motivation

Motivations Relaxation and Escape 1.To escape daily routine and pressure of life 2.To relax both physically and psychologically 3. To relax and take things easy 4.To be liberated from daily routine, seek time for my own 5.Relieve stress and tension 6.Get a break from everyday job Destination Experience 1.To interact with local people 2.To study the local culture, history and society 3.To experience the local way of life 4.To seek new and unforgettable experience 5.To enjoy local natural landscape 6.To enjoy local cultural landscape 7.To achieve harmony between human and nature 8.To learn something new/ increase knowledge Self Improvement and Development 1.To know and understand myself 2.To improve personal skills 3.To develop personal capacity 4.To change my characters 5.To accomplish/ achieve something 6.To fulfill an ambition Social Interaction 1.To make new friends 2.To develop a new friendship 3.To communicate with and learn from other backpackers 4.To share feelings and build up connections with family and friends 5.To build friendship with others

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Appendix 2 Measurement Items for Constraints

Constraint Intrapersonal 1.I am not confident of doing backpacking 2.I am not confident in my skills to go backpacking (understanding maps, communicate with strangers, etc) 3.I worry about my personal safety 4.I worry backpacking involves too many risks Interpersonal

1.I do not have backpacking companions 2.People with whom I would go backpacking are not interested in going with me

3.My family/ friends do not support me going backpacking 4.It is difficult to coordinate holiday with my family/ friends 5.People with whom I would go backpacking are on different schedules Structural

1.Backpacking costs too much money 2.School/ work keeps me too busy to go backpacking 3.The places I want to go backpacking are too far 4.The destinations are poorly developed and maintained

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Appendix 3 Measurement Items for Negotiation Strategies

Negotiation Strategies Cognitive Strategies 1.I ignore problems resulting from going backpacking

2.I push myself harder when I encounter some obstacles while deciding to go backpacking 3.I persist until I overcome obstacles while deciding to go backpacking 4.I stay positive when I encounter obstacles while deciding to go backpacking 5.I accept the constraints I have and do my best to solve them Time Management 1.I adjust my schedule to go backpacking 2.I reorganize my schedule 3.I plan ahead and save time for backpacking 4.I try to make plan to better balance my life Interpersonal Coordination 1.I try to find people with similar interests 2.I try to find people who could go backpacking with me 3.I try to find friends to go backpacking with me 4.I try to persuade people to go backpacking with me Money Management 1.I budget my money 2.I think of how I could save money before going backpacking

3.I try not to spend too much money when going backpacking 4.I find a way to earn some money before going backpacking

Appendix 4 Measurement Items for Travel Intention

Travel Intentions 1.I intend to go backpacking more often over the next 12 months 2.I am determined to go backpacking more often over the next 12 months 3.I am likely to go backpacking more often over the next 12 months 4.I will go backpacking more often over the next 12 months if my family or friends go with me

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Appendix5 Questionnaire

Questionnaire 1. What sex are you?  Male  Female  Choose not to respond 2. What is your birth year? ______3. What is your education level？  Secondary or below  Technical/ vocational school  Bachelor’s degree  Master’s degree or above 4. What is your employment status（ if you are a student working as a part time, please chose “ student”）？  Student  Employed part time  Employed full time  Temporarily unemployed/looking for work  Retired 5. What is your personal monthly income (RMB)?  <1500  1500-3000  3001-4500  4501-6000  6001-7500  >7500  Choose not to respond 6. How many times have you gone backpacking in the past 12 months? ______7. What was the duration of your last backpacking trip?

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 8 days or less  9 to 14 days  15 to 21 days  22 days and above

Section 1

Description: this section is assessing your travel behaviors and travel preferences to better identify Chinese backpackers.

For each of the question below, please choose a number from 1 to 5 to indicate how much you agree with the statement, where: 1= Strongly Disagree, 2 = Disagree, 3 = Undecided, 4 = Agree, 5=Strongly disagree

Behaviors Strongly Disagre Undecid Agree Strongly Disagre e ed Agree e 1.When I go backpacking, I travel under 1 2 3 4 5 a tight budget 2.When I go backpacking, I travel with a 1 2 3 4 5 flexible timetable. 3.When I go backpacking, I prefer 1 2 3 4 5 staying in a hostel. 4.When I go backpacking, I want to 1 2 3 4 5 experience the local culture as much as possible. 5.When I go backpacking, I look for 1 2 3 4 5 travel information from travel websites rather than reading travel guidebooks. 6.When I go backpacking, I prefer 1 2 3 4 5 traveling in groups. 7.When I go backpacking, I prefer doing 1 2 3 4 5 some outdoor activity such as hiking, trekking and camping

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Section 2 Description: This section is assessing what you are looking for while going backpacking.

For each of the question below, please choose a number from 1 to 5 to indicate how much you agree with the statement, where: 1= Strongly Disagree, 2 = Disagree, 3 = Undecided, 4 = Agree, and 5 = Strongly Agree.

When I go backpacking in a new destination, I am looking for......

Strongly Disagree Undecid Agree Strongly disagree ed agree 1.To escape daily routine and pressure of life 1 2 3 4 5 2.To relax both physically and 1 2 3 4 5 psychologically 3. To relax and take things easy 1 2 3 4 5 4.To be liberated from daily routine, seek 1 2 3 4 5 time for my own 5.Relieve stress and tension 1 2 3 4 5 6. Get a break from everyday job 1 2 3 4 5 Strongly Disagree Undecid Agree Strongly disagree ed agree

1.To interact with local people 1 2 3 4 5 2.To study the local culture, history and 1 2 3 4 5 society 3.To experience the local way of life 1 2 3 4 5 4.To seek new and unforgettable experience 1 2 3 4 5 5.To enjoy local natural landscape 1 2 3 4 5 6.To enjoy local cultural landscape 1 2 3 4 5 7.To achieve harmony between human and 1 2 3 4 5 nature 8. To learn something new/ increase 1 2 3 4 5 knowledge

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I am hoping to make some changes about myself such as......

Strongly Disagree Undecid Agree Strongly disagree ed agree 1.To know and understand myself 1 2 3 4 5 2.To improve personal skills 1 2 3 4 5 3.To develop personal capacity 1 2 3 4 5 4.To change my characters 1 2 3 4 5 5.To accomplish/ achieve something 1 2 3 4 5 6.To fulfill an ambition 1 2 3 4 5

When I interact with people while going backpacking, I am looking.....

Strongly Disagree Undecid Agree Strongly disagree ed agree 1.To make new friends 1 2 3 4 5 2.To develop a new friendship 1 2 3 4 5 3.To communicate with and learn from other 1 2 3 4 5 backpackers 4.To share feelings and build up connections 1 2 3 4 5 with family and friends 5.To build friendship with others 1 2 3 4 5

Section 3 Description: This section is assessing what might prevent you going backpacking.

For each of the question below, please choose a number from 1 to 5 to indicate how much you agree with the statement, where: 1= Strongly Disagree, 2 = Disagree, 3 = Undecided, 4 = Agree, and 5 = Strongly Agree.

When deciding to go backpacking......

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Strongly Disagree Undecid Agree Strongly disagree ed agree

1.I am not confident of doing backpacking 1 2 3 4 5 2.I am not confident in my skills to go 1 2 3 4 5 backpacking (understanding maps, communicate with strangers, etc) 3.I worry about my personal safety 1 2 3 4 5 4.I worry backpacking involves too many 1 2 3 4 5 risks Strongly Disagree Undecid Agree Strongly disagree ed agree

1.I do not have backpacking companions 1 2 3 4 5 2.People with whom I would go backpacking 1 2 3 4 5 are not interested in going with me 3.My family/ friends do not support me going 1 2 3 4 5 backpacking 4.It is difficult to coordinate holiday with my 1 2 3 4 5 family/ friends 5.People with whom I would go backpacking 1 2 3 4 5 are on different schedules

Strongly Disagree Undecid Agree Strongly disagree ed agree 1.Backpacking costs too much money 1 2 3 4 5 2.School/ work keeps me too busy to go 1 2 3 4 5 backpacking 3.The places I want to go backpacking are too 1 2 3 4 5 far 4.The destinations are poorly developed and 1 2 3 4 5 maintained

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Section 4

Description: This section is assesses how you solve constraints that you encounter when going backpacking.

For each of the question below, please choose a number from 1 to 5 to indicate how much you agree with the statement, where: 1= Strongly Disagree, 2 = Disagree, 3 = Undecided, 4 = Agree, and 5 = Strongly Agree.

When I run into problems I deal with them as follows:

Strongly Disagree Undecid Agree Strongly disagree ed agree

1.I ignore problems resulting from going 1 2 3 4 5 backpacking 2.I push myself harder when I encounter 1 2 3 4 5 some obstacles while deciding to go backpacking 3.I persist until I overcome obstacles while 1 2 3 4 5 deciding to go backpacking 4.I stay positive when I encounter obstacles 1 2 3 4 5 while deciding to go backpacking 5. I accept the constraints I have and do my 1 2 3 4 5 best to solve them If I believe that I do not have enough time to go backpacking,......

Strongly Disagree Undecid Agree Strongly disagree ed agree 1.I adjust my schedule to go backpacking 1 2 3 4 5 2.I reorganize my schedule 1 2 3 4 5 3.I plan ahead and save time for backpacking 1 2 3 4 5

4.I try to make plan to better balance my life 1 2 3 4 5 If I do not have backpacking companions,......

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Strongly Disagree Undecid Agree Strongly disagree ed agree 1.I try to find people with similar interests 1 2 3 4 5 2.I try to find people who could go 1 2 3 4 5 backpacking with me 3.I try to find friends to go backpacking with 1 2 3 4 5 me 4.I try to persuade people to go backpacking 1 2 3 4 5 with me

If I worry about money for backpacking,......

Strongly Disagree Undecid Agree Strongly disagree ed agree 1.I budget my money 1 2 3 4 5 2.I think of how I could save money before 1 2 3 4 5 going backpacking 3.I try not to spend too much money when 1 2 3 4 5 going backpacking 4.I find a way to earn some money before 1 2 3 4 5 going backpacking

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Section 5 Description: This section is assessing how much you are interested in going backpacking over the next 12 months. For each of the question below, please choose a number from 1 to 5 to indicate how much you agree with the statement, where: 1= Strongly Disagree, 2 = Disagree, 3 = Undecided, 4 = Agree, and 5 = Strongly Agree.

Strongly Disagree Undecid Agree Strongly disagree ed agree 1.I intend to go backpacking more often over 1 2 3 4 5 the next 12 months 2.I am determined to go backpacking more 1 2 3 4 5 often over the next 12 months 3. I am likely to go backpacking more often 1 2 3 4 5 over the next 12 months 4.I will go backpacking more often over the 1 2 3 4 5 next 12 months if my family or friends go with me

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Appendix 6 REB Approval Letter

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Appendix 7 Reusults of Pilot Test 1- Motivation

Cronbach's Cronbach's alpha if items Construct and Items alpha deleted Motivation 0.771 Escape and Relaxation 0.349 To escape daily rountine and pressure of life 0.211 To relax both physically and psychologically 0.301 To get more resh air because of confusion about the future 0.432 To be liberated from social norms 0.336 To achieve balance in life 0.187 Destination Experiences 0.436 To interact with local people 0.395 To study the local culture, history and society 0.389 To expereince local way of life 0.457 To seek adventure and exciting experiences 0.428 To view natural landscape 0.371 To view culutral landscape 0.367 To achive harmony between human and nature 0.382 Self exploration and improvement 0.644 To know and understand myself 0.592 To improve personal skills 0.528 To develop personal capacity 0.565 To change my characteristics 0.612 Social Interaction 0.527 To make new friends 0.457 To seek for other half of my life (a relationship/ a partner) 0.344 To communicate with and lerarn from other backpackers 0.397 To share feelings and build up connections with family and friends 0.47 To make me different from others 0.644 KMO=0.547

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Appendix 8 Results of Pilot test 1- Constriant

Cronbach's Cronbach's alpha if items Construct and Items alpha deleted Constraint 0.818 Intrapersonal constraint 0.755 I am not confident of traveling a long distance/ unfamiliar places 0.645 I am not confident at my skills to go backpacking (understanding maps, communicate with strangers, etc) 0.745 I worry about my personal safety 0.692 Backpacking involves too many risks 0.71 Interpersonal constraint 0.606 I do not have backpacking companions 0.522 My family does not support me to go backpacking 0.473 My peers will judge me if I go backpacking 0.586 It is difficult to coordinate holidays with my family/ friends 0.495 Social prejudice to go backpacking 0.636 Strucutral constraint 0.638 I do not have enough money to go backpacking 0.677 School/ works keeps me too busy to go backpacking 0.515 The places I want to go backpacking are too far 0.473 The destinations are poorly developed and maintained 0.579 KMO=702 Appendix 9 Results of Pilot Test 1- Negotiation Strategies

Cronbach's Cronbach's alpha if items Construct and Items alpha deleted Negotiation Strategies 0.357 Cognitive Strategies 0.336 I try to ignore some problems resulting from going backpacking 0.345 I try to push myself harder when I encounter some obstacles while deciding to go backpacking 0.118 I try to persist until I overcome obstacles while deciding to go backpacking 0.25 I try to swallow my pride when I encounter some obstacles while deciding to go backpacking 0.366 Behaviroal Strategies 0.185 I try to organize my schedule 0.12 I try to budget my money 0.366 I try to find people with similar interests -0.042 I try to persuade my family or friends to go backpacking 0.219 I try to improve my backpacking skills 0.225

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I try to choose a safe place to travel -0.029 KMO=0.418 Appendix 10 Results of Pilot Test 2- Motivation

Cronbach's Cronbach's alpha if items Construct and Items alpha deleted Motivation 0.591 Escape and Relaxation 0.256 To escape daily rountine and pressure of life 0.205 To relax both physically and psychologically 0.172 To get a break from everyday job 0.173 To achieve balance between work and life 0.267 Destination Experiences 0.171 0.187 To interact with local people -0.022 To study the local culture, history and society 0.153 To learn about/ experience other culture 0.166 To view local landsacpe 0.344 To increase my knowledge of destination -0.082 Self exploration and improvement 0.533 To know and understand myself 0.541 To improve personal skills (such as communication skills) 0.359 To develop personal capacity 0.384 To develop my personality 0.535 Social Interaction 0.552 To make new friends 0.415 To communicate with and lerarn from other backpackers 0.508 To share feelings and build up connections with people 0.422 To have a good time with friends 0.561 KMO=0.447

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Appendix 11 Results of Pilot Test 2- Constraint

Cronbach's Cronbach's alpha if items Construct and Items alpha deleted Constraint 0.863 Intrapersonal constraint 0.832 I am not confident of doing backpacking 0.871 I am not confident at my skills to go backpacking (understanding maps, communicate with strangers, etc) 0.767 I worry about my personal safety 0.745 I worry backpacking involves too many risks 0.724 Interpersonal constraint 0.821 I do not have backpacking companions 0.821 People with whom I would go backpacking are not interested in going with me 0.77 My family / friends do not support me to go backpacking 0.751 It is difficult to coordinate holidays with my family/ friends 0.795 People with whom I would go backpacking are on different schedules 0.779 Strucutral constraint 0.605 Backpacking costs too much money 0.641 School/ works keeps me too busy to go backpacking 0.509 The places I want to go backpacking are too far 0.489 The destinations are poorly developed and maintained 0.466 KMO=0.734

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Appendix 12 Results of Pilot Test 2- Negotiation Strategies

Cronbach's Cronbach's alpha if items Construct alpha deleted Negotiation Strategies 0.646 Cognitive Strategies 0.235 I ignore problems resulting from going backpacking 0.097 I persist until I overcome obstacles while deciding to go backpacking 0.139 I stay positive when I encounter obstacles while deciding to go backpacking 0.172 I accept the constraints I have and do my best to solve them 0.33 Time Management 0.156 I adjust my work/ school schedule to go backpacking -0.064 I reorganize my schedule 0.082 I plan ahead and save time for backpacking 0.387 I try to make plan to better balance my life -0.044 Interpersonal Coordination 0.57 I try to find people with similar interests 0.447 I try to find people who can go backpacking with me 0.481 I try to find people in backpacking community 0.378 I try to persuade my family and friends to go backpacking with me 0.643 Money Management 0.742 I budget my money 0.586 I think of how I could save money before going backpacking 0.66 I try not to spend too much money when going backpacking 0.65 I find a way to earn some money before going backpacking 0.816 KMO=0.500

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Appendix 13 Results of Pilot Test 3- Motivation

Cronbach's Cronbach's alpha if items Construct and Items alpha deleted Motivation 0.851 Escape and Relaxation 0.243 To escape daily rountine and pressure of life 0.296 To relax both physically and psychologically 0.321 To relax and take things easy 0.115 To be liberated from daily rountine, seek time for my own 0.181 Relieve stress and tension 0.148 Get a break from everyday job 0.165 Destination Experiences 0.605 To interact with local people 0.529 To study the local culture, history and society 0.567 To experience the local way of life 0.588 To seek new and unforgettable experience 0.564 To enjoy local natural landscape 0.563 To enjoy local cultural landscape 0.609 To achieve harmony between human and nature 0.596 To learn somethihng new/ increase knowledge 0.561 Self exploration and improvement 0.623 To know and understand myself 0.563 To improve personal skills (such as communication skills) 0.503 To develop personal capacity 0.63 To change my characters 0.635 To accomplish/ achieve something 0.588 To fulfill an ambition 0.534 Social Interaction 0.704 To make new friends 0.57 To develop a new friendship 0.587 To communicate with and lerarn from other backpackers 0.701 To share feelings and build up connections with people 0.766 To build friendship with others 0.607 KMO=0.646

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Appendix 14 Results of Pilot Test 3- Constraint

Cronbach's Cronbach's alpha if items Construct and Items alpha deleted Constraint 0.875 Intrapersonal constraint 0.824 I am not confident of doing backpacking 0.73 I am not confident at my skills to go backpacking (understanding maps, communicate with strangers, etc) 0.858 I worry about my personal safety 0.768 I worry backpacking involves too many risks 0.745 Interpersonal constraint 0.735 I do not have backpacking companions 0.718 People with whom I would go backpacking are not interested in going with me 0.663 My family / friends do not support me to go backpacking 0.718 It is difficult to coordinate holidays with my family/ friends 0.673 People with whom I would go backpacking are on different schedules 0.672 Strucutral constraint 0.745 Backpacking costs too much money 0.698 School/ works keeps me too busy to go backpacking 0.645 The places I want to go backpacking are too far 0.673 The destinations are poorly developed and maintained 0.721 KMO=0.706

Appendix 15 Results of Pilot Test 3- Negotiation Strategies

Cronbach's Cronbach's alpha if items Construct alpha deleted Negotiation Strategies 0.789 Cognitive Strategies 0.712 I ignore problems resulting from going backpacking 0.659 I push myself harder when I encounter some obstacles while deciding to go backpacking 0.657 I persist unitil I overcome obstacles while deciding to go backpacking 0.614 I stay positive when I encounter obstacles while deciding to go backpacking 0.712 I accept the constraints I have and do my best to solve them 0.672 Time Management 0.398 I adjust my schedule to go backpacking 0.43 I reorganize my schedule 0.327

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I plan ahead and save time for backpacking 0.199 I try to make plan to better balance my life 0.332 Interpersonal Coordination 0.653 I try to find people with similar interests 0.639 I try to find people who could go backpacking with me 0.464 I try to find friends to go bakcpacking with me 0.613 I try to persuade my family and friends to go backpacking with me 0.604 Money Management 0.226 I budget my money 0.292 I think of how I could save money before going backpacking 0.046 I try not to spend too much money when going backpacking 0.16 I find a way to earn some money before going backpacking 0.183 KMO=0.480

Appendix 16 Exploratory factor analysis of pilot test 3- Motivation

Factors Factor loadings Eigenvalue Self Growth ( α=0.785) 4.205 To know and understand myself 0.727 To change my characters 0.720 To make new friends 0.638 To develop a new friendship 0.627 Culture Learning ( α=0.712) 1.620 To interact with local people 0.809 To study the local culture, history and society 0.737 To experience the local way of life 0.660 To communicate with and learn from other backpackers 0.561 Self fulfillment ( α=0.782) 1.410 To improve personal skills 0.852 To accomplish / achieve something 0.832 To build friendship with others 0.609 Destination Experience (α=0.482) 1.221 To achieve harmony between human and nature 0.680 To seek new and unforgettable experiences 0.638 KMO=0.646, explained 62% of the variance

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Appendix 17 Exploratory factor analysis of pilot test 3- Constraint

Factors Factor loadings Eigenvalue Intrapersonal constraint (α=0.824) 4.968 I am not confident of doing backpacking 0.811 I am not confident at my skills to go backpacking (understanding maps, communicate with strangers, etc) 0.663 I worry about my personal safety 0.757 I worry backpacking involves too many risks 0.799 Interpersonal constraint(α=0.718) 1.688 People with whom I would go backpacking are not interested in going with me 0.704 My family / friends do not support me to go backpacking 0.696 It is difficult to coordinate holidays with my family/ friends 0.704 People with whom I would go backpacking are on different schedules 0.721 Strucutral constraint(α=0.745) 1.173 Backpacking costs too much money 0.67 School/ works keeps me too busy to go backpacking 0.71 The places I want to go backpacking are too far 0.771 The destinations are poorly developed and maintained 0.614 KMO=0.733, explained 60% of the variance

Appendix 18 Exploratory factor analysis of pilot test 3- Negotiation Strategies

Factor Eigenval Factors loadings ue Interpersonal coordination ( α=0.634) 2.614 I try to find people who could go backpacking with me 0.732 I try to find friends to go backpacking with me 0.787 I try to persuade people to go backpacking with me 0.762 Trip preparedness ( α=0.640) 1.655 I think of how I could save money before going backpacking 0.821 I try to make plan to better balance my life 0.656 I push myself haefer when I encounter some obstacles while deciding to go backpacking 0.74 Cognitive strategies ( α=0.691) 1.352 I ignore problems resulting from going backpacking 0.856 I persist until I overcome obstacles while deciding to go backpacking 0.84 Time management (α=0.529) 1.151 I reorganize my schedule 0.793 I plan ahead and save time for backpacking 0.783 KMO=0.503, explained 62% of the variance

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