Factors affect vietnamese’s repurchase intention to choose airbnb relationship between past experience and the impact of covid 19 m a thesis major international hospitality and tourism management

Factors Affect Vietnamese’s Repurchase Intention To Choose Airbnb: Relationship Between Past Experience And The Impact Of Covid-19.. Accordingly, the aim of this study is to examine the

Factors Affect Vietnamese’s Repurchase Intention To Choose Airbnb: Relationship Between Past Experience

And The Impact Of Covid-19

A dissertation submitted by

Ngoc Thi Tran

in partial completion of the award of

MSc International Hospitality and Tourism Management

'I hereby declare that the dissertation submitted is wholly the work of

Ngoc Thi Tran

Any other contributors or sources have either been referenced

in the prescribed manner or are listed in the acknowledgements

together with the nature and scope of their contribution.'

Faculty of Management Bournemouth University

2020

ii

DECLARATION

I confirm that this dissertation contains information of a commercial or confidential nature or includes personal information other than that which would normally be in the public domain and that it must not be made available for public access

Ethical and Health & Safety issues

I confirm that the on-line ethics checklist was completed and that any ethical considerations associated with the proposed research were discussed with my supervisor and an appropriate research strategy was developed which would take them into account I also confirm that any potential health & safety risks associated with the proposed research were discussed with my supervisor and where necessary, appropriate precautions were documented, including an appropriate risk assessment

Copyright

The copyright for this dissertation remains with me

Requests for Information

I agree that this dissertation may be made available as the result of a request for information under the Freedom of Information Act

Abstract

Airbnb, which considered as a part of sharing economy system, is a quickly expanding industry and has brought people’s attention in various ways In Vietnam, Airbnb appears from 2015 and since then attracting millions of both customers and hosts whose renting their own property to tourists every day Living in and homestay such as Airbnb is a way to create a novel experience and it shows an increase in demand in recent years While this phenomenon showing remarkable growth in term of the number Airbnb around Viet Nam There is a lack of academic literature related to motivations and factors that affect tourist repurchase intention when choosing Airbnb as accommodation for their next trips Furthermore, over the last few months, the breaks out of the pandemic (Covid-19) has led to a significant impact on the tourism industry Airbnb also has a serious influence on the revenue due to countries lockdown and transportation have stopped around the world

During this unstable period, there is a need to examine how the current situation affects customer behaviour and how their previous experience secures their perceived value of Airbnb Accordingly, the aim of this study is to examine the relationship between past experience and perceived value, to evaluate the impact of COVID-19 on customer risk perception and to see the relationship between value and risk perception on repurchase intention

A quantitative method is used in order to test the hypothesis proposed by the researcher, an online survey was conducted and then using the SPSS software to analyze the data collected The finding of this research indicated that while economic benefit, usefulness website, home benefit, host-guest relationship and authenticity have an impact on customer perceived value, Covid-19 increase risk perception of tourist, therefore, decrease Airbnb repurchase intention Host-Guest relationship contributes a considerable impact on perceived value and overall perceived value largely decide customer repurchase intention In contract, perceived risk indicates a little impact on repurchase intention even in this unstable period At the end of the research, suggestions for developers is mentioned for future improvement

Word count: 14.172

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Table of Contents

Abstract 0

Chapter 1 Introduction 6

1.1 Background to the topic 6

1.2 Reasons for choosing the topic 7

1.2.1 Academic rationale 7

1.3 Industry rationale 7

1.4 Research aim and objectives 7

1.5 Structure of the dissertation 8

Chapter 2 Literature review 9

2.1 Introduction 9

2.2 Airbnb 9

2.2.1 Airbnb phenomenon 9

2.2.2 Studies on Airbnb 10

2.3 Repuchase intention in Airbnb 11

2.4 Perceived value 12

2.4.1 Perceived usefulness 13

2.4.2 Economic benefits 13

2.4.3 Household benefits 13

2.4.4 Host guest relationship 14

2.4.5 Perceived Authenticity 15

2.5 Perceived risk 15

2.5.1 Perceived risk in a crisis (Covid-19 pandemic) 17

2.6 Hypothesis 18

2.7 Research gaps 19

Chapter 3 Methodology 20

3.1 Introduction 20

3.2 Research Philosophies 20

3.3 Research Approach 21

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3.4 Secondary research 21

3.5 Primary research 22

3.5.1 Quantitative analysis 23

3.6 Questionnaire design 23

3.7 Sampling and sample size 26

3.7.1 Sampling 27

3.7.2 Sample size 27

3.8 Pilot test 28

3.9 Data analysis 29

3.10 Conclusion 29

Chapter 4 Finding and Analysis 30

4.1 Introduction 30

4.2 Descriptive Analysis 30

4.2.1 Demographic characteristic 30

4.2.2 General data analysis 31

4.3 Reliability Analysis 33

4.4 Validity Analysis 34

4.5 Research Variable Descriptive Analysis 37

4.6 Correlation Analysis 38

4.6.1 Correlation Analysis between PV and other Research Variables 38

4.6.2 Correlation Analysis between PR and Covid-19 39

4.6.3 Correlation Analysis between RI, PV and PR 39

4.6.4 Conclusion 40

4.7 Regression Analysis 40

4.7.1 Regression Analysis for PV and Other Research Variables 41

4.7.2 Regression Analysis for COVID 19 and PR 43

4.7.3 Regression Analysis for RI, PV and PR 44

4.7.4 Conclusion 46

4.8 Hypothesis test 46

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Chapter 5 Conclusions and Recommendations 47

5.1 General conclution 47

5.2 Academic contribution 48

5.3 Recommendations for industry 49

5.4 Limitation and implications for future research 49

References 51

Appendices 60

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LIST OF TABLES

Table 3.1: Questionnaire design 26

Table 4.1: Demographic characteristic analysis 31

Table 4.2: The number of Airbnb stay 31

Table 4.3: Airbnb stay purpose 32

Table 4.4: House type 32

Table 4.5: Geographic choice 33

Table 4.6: Reliability Analysis value 34

Table 4.7: KMO and Bartlett's Test value 35

Table 4.8: Factor Loading value 37

Table 4.9: Research Variable Descriptive Analysis value 37

Table 4.10: Correlation Analysis between PV and other research variables 39

Table 4.11: Correlation Analysis between PR and Covid-19 39

Table 4.12: Correlation Analysis between RI, PV and PR 40

Table 4.13: Model Summary for PV and Other Research Variables 41

Table 4 14: ANOVA of PV and PE 41

Table 4 15: Coefficients of PV and PE 42

Table 4.16: Model Summary of Covid-19 and PR 43

Table 4.17: ANOVA of Covid-19 and PR 44

Table 4.18: Coefficientsanalysis of Covid-19 and PR 44

Table 4.19: Model Summary of RI, PV, and PR 44

Table 4.20: ANOVA of RI, PV, PR 45

Table 4.21: Coefficients of RI, PV, PR 46

Table 4.22: Hypothesis test 47

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LIST OF FIGURES

Figure 2.1: Model conceptual 18

Figure 3.1: The Comparison between Positivistic Philosophy and Phenomenology (Amended from Collis and Hussey (2003) 21

Figure 3.2: Sampling technique (Israel 1992) 27

Figure 3.3: Sample size equation (Israel 1992) 28

Figure 4.1: Cronbach’s apha value (Tolmie et al 2011) 33

LIST OF ABBREVIATIONS

SE: Sharing Economy

PV: Perceived value

PR: Perceived risk

RI: Repurchase intention

EFA: exploratory factor analysis

KMO: Kaiser-Meyer-Olkin

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Chapter 1 Introduction

1.1 Background to the topic

The sharing economy (SE) is considered as a disruptive business model that commenced in the evolution of Internet technologies and specifically Web 2.0 (Guttentag and Smith 2017; Hall and Williams 2020) Sharing is an old concept, however, the sharing of products and services between strangers for-profit are emerging in recent decades as the emerge of digital technologies (Belk 2010; Frenken and Schor 2017) There are a range of diference terms are used interchangeably with SE such as collaborative economy or peer to peer economy (Guttentag et al 2017) In 2015, the definition of SE officially introduced from the Oxford Dictionaries as: “An economic system in which assets/services are shared between private individuals, either for free or for a fee, typically by means of the Internet”

This share model is bringing change in term of shared resource, business model and customer behavior in several industries including Tourism (Pusshmann) Generally, notions of the SE in tourism can be divided into four groups, namely: transportation (e.g Uber, Grab), dining (e.g Eatwith), tour guide services (e.g Vayable), and accommodation (e.g Airbnb, Homeaway, Couchsurfing) (Ert et al., 2016) Organizations such as Airbnb position themselves as part of the sharing economy

In Vietnam, Airbnb appears from 2015 and since then attracting millions of both customers and hosts whose renting their own property to tourists every day After just four year, there are more than 50.000 Airbnb listing around the country Living in and homestay such as Airbnb is a new way to create a unique experience and it is showing a sharply increase in the demand

There are a number of studies have been conducted to investigate subject related to Airbnb since it is established in 2007 The common studies must be mentioned such as satisfaction experience about the Airbnb (Bai et al 2008; Fang et al 2014; Möhlmann 2015), customer motivations (Johnson 2013; Guttentag et al 2017; Tran and Filimonau 2020), some research compares Airbnb with the hotel industry (Tussyadiah and Zach 2015; McGowan and Mahon 2018; Li et al 2020) At the same time, more and more researchers interested in determining factors that could affect the repurchase intention (RI) in recent year (Matute et al 2016; Liang

et al 2017; Amaro et al 2018)

According to Liang et al (2017), RI can determine by comparing perceived value (PV) and perceived risk (PR) that the customer receives when booking Airbnb The researcher explores that price, unique experience and good e-word of mouth are significantly crucial to RI This result is also support for Matute et al (2016) finding regarding e-word of mouth influence toward purchase intention Meanwhile, two research of Amaro et al (2017) and Amaro et al

RI toward Airbnb The importance of RI has been demonstrated by many studies However, there are a few literature resources regarding the RI in Airbnb context, especially in developing countries such as Viet Nam Moreover, this study intends to investigate the RI in an unstable period which is the pandemic happened in this recent time There is some risk assessment research from An et al (2010), Chiu et al (2014) and Jun (2020) related to tourism that the researcher believes could apply and adapt to build a new model for this study Hopefully, this study can fulfil the gaps in the literature, as well as the results of the research, can help to gain

a better comprehension about this area and motivate further research on this topic in future

1.4 Research aim and objectives

The main purpose of this study is to “explore and identify the factors that influence Vietnamese travellers’ Airbnb repurchase intention in the post-pandemic (COVID-19) context.”

Hence, the following objectives need to be achieved:

4 To give possible recommendations for further research

In order to make a valid and comprehensive research of the topic, appropriate research techniques are required to be employed in this study

1.5 Structure of the dissertation

This study is divided into five chapters Each chapter is summarily described as below:

Chapter 1: Introduction

The first chapter introduces the relevant topic background and the academic and practical reasons for choosing this dissertation topic The aim and objectives are mentioned as well Chapter 2: Literature Review

In the next chapter, the researcher reviews the exiting literature related to the topic including Airbnb establishment and the antecedent factors of RI which will be examined in chapter 3 The purpose here is to review all exit academic resources of the information relevant to the topic these resources are selected from books, journals, reports and other sources from the online library and the internet network

Chapter 3: Research Methodology

In order to reach the aim and objectives proposed from the beginning, particular research technique is used in this chapter to determine sampling, sample size, design questionnaire, collect data and specifying data analysis method will be applied in the next chapter

Chapter 4: Finding and analysis

This chapter presents the main findings, after the data collection process The SPSS system is used to produce the result, findings are also mentioned and discuss

Chapter 5: Conclusion and Recommendations

The final chapter restates the aim and objectives to give discussion Summarizes of the results

is provides After that academic contributions and recommendations for the industry also presented, following by limitations and implications for future research

2.2 Airbnb

2.2.1 Airbnb phenomenon

Positioning the company with its business model is the sharing economy (Oskam & Boswijk, 2016), Airbnb emerges rental market as a tech-unicorn company (Airbnb 2020) The start up use spare resourse and technology to provide an innovation business model This platform is an online marketplace allowing people to list, search and book an accommodation in the short term (Bloomberg 2018) The estimate statistics from 2019 show that Airbnb accounts for roughly 20% of the short-term rental market globally With the entire market valued approximately $87 Billion in 2020, this is forecasted to bring a total revenue up to $20Billion for Airbnb However, these growth numbers are now likely to be significantly challenged by the influence of travel decline amid COVID-19 pandemic (Hall et al., 2020) In fact, Airbnb had to lay off 25 percent

of its workforce and 2020 revenue could fall by half due to the outspread of the pandemic (Khan 2020)

Even so, the Airbnb number of properties listing on its website is now up to 7 million worldwide (Kastrenakes 2020), Airbnb is considered the largest lodging provider in the world (Tran and Filimonau 2020) However, the company does not own any property, instead, it act as a broker receiving booking commission from hosts and guests (Sraders 2018) Guests can look for suitable accommodation by using filters such as location, room type, dates and price, and can search for specific types of houses, such as unique homes, bed and breakfasts or vacation houses (Statt 2018) Similar to the traditional accommodation booking site, customers also need to provide personal information and conduct the payment in advance depending on the host's payment policy Through the website, hosts provide their property information such as prices, the number of guest allowance, location, home type, amenities, and rules Guests can have a conversation with hosts by using the chatbox system Both Hosts and guests could leave reviews about their experience with the other side (Yu 2012, Sraders 2018)

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Airbnb is considered as a disruptor which has caused a variety of contrary opinion in the lodging industry On the one hand, it is argued that this model has a lot of socio-economic benefits, some scholars believe that sharing accommodation expand destination selection, increase travel frequency, length of stay and the range of activities participated in tourism destination (Tussyadiah and Péonen 2015; Heo 2016) There is also a belief that Airbnb does not compete with hotels due to its appeal to a different market segment Visitors choose Airbnb to experience more authentic local experiments with affordable cost (Guttentag, 2015; Dogru et al 2020) as hotels are run by professionals and visitors experience an impersonal "corporate" experience Share home, instead, provides guests a sense of feeling at home, interact with the host family, first-hand relationship with locals, experience the local culture, and low-cost accommodation (Byers et al 2013; Kulshreshtha & Kulshrestha, 2019)

On the other hand, many studies claimed that Airbnb effect traditional hotel, especially the end market (Roma et al 2019;Guttentag and Smith 2017; Kuo 2020) Furthermore, some studies show that Airbnb increases long-term rent in many regions, due to the fact that landlords switch to short-term rentals to receive higher returns through Airbnb (Thompson 2018) Attitude toward P2P accommodation is divided into two groups The first group saw P2P as a threat to tourism Generally, accommodation sectors and governments support this thought and criticized P2P accommodation for providing reduces job security, unfair competition, poses a threat to safety and avoids taxes (Juul 2015) In contract, both startups and passengers have a commonly positive opinion towards sharing property and promote this platform, it is creating job opportunities, provide economical price stay and thus extend travellers’ length of stay (Dolnicar, 2018)

low-2.2.2 Studies on Airbnb

Due to the new appearance of this platform, Airbnb research concept is slightly limited and have a short history (from 2008 to 2020), addressing in a number of topics Some researches focused on the provider's side whose renting their own property such as the hosts’ motivation

on why they want to list and make money from Airbnb (Stern 2014; Gibbs et al 2018; Xie and Chen 2019), the behaviour of the Host to the customer (Li et al 2015), policy and regulation concerns (Lee 2016; Edelman and Geradin 2015; Uzunca and Borlenghi 2019), the Airbnb platform system (Fradkin et al 2014; Ert et al 2015), or Airbnb’s branding procedures (Yannopoulou et al 2013; Roma et al 2019) Additionally, others researchers investigated the influence of Airbnb on the traditional hotel industry (Neeser et al 2015; Zervas et al 2014), on the local community (Guttentag 2013), or on the working environment (Fang et al 2015)

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There are also studies that examined Airbnb consumer experiences Guttentag (2015), for example, described the innovation of Airbnb as a disruption on the traditional market He found that economical expense is the main driver for people engaging with this innovative platform, although the judgment that Airbnb offers lower price has been partly questioned by Lane and Woodworth’s (2016) study The study pointing that in some of the urban United States regions, Airbnb actually not the cheaper choice Sometimes, the average rate of Airbnb accommodation was more expensive than the (small) hotels in the same area

In the other perspective, Tran and Filimonau (2020) examined the drivers and impediments of the use of home-sharing services from the consumers’ view They found that local community, past experiences, sustainability, and economic benefits are the main factor that drives customer joining to Airbnb, conversely, the lack of perceived value and lack of trust with regards to technology are the determinants that restrain user's motivations These findings are recognised

by the results of the study of Guttentag et al (2017) To sum up, the literature researches on Airbnb have broadly examined on diverse areas, but only a few have discussed what factors affect Airbnb consumers’ RI Besides, most of the literature has been tested by the qualitative method, while this study will approach the quantitative side

2.3 Repuchase intention in Airbnb

Repurchase intention represents “the individual's judgement about buying again a designated service from the same company, taking into account his or her current situation and likely circumstances” (Hellier et al 2003) Several previous studies have explored RI in the online context, while various antecedents, as well as research models, were examined (Wu and Chang 2007; An et al 2010; Chiu et al 2012; Fang et al 2014; Matute et al 2016; Talón-Ballestero et

al 2019) Among the reviewed articles, the intention to continue purchase seems to be dominated by internal factors such as satisfaction, trust, and the customer's technology awareness or external factor including social media, information quality, electronic word-of-mouth, and brand credibility

RI in Airbnb context also popular examined by scholars in the period from 2014 to 2020 ((Matute et al 2016; Tussyadiah and Pesonen 2016; Liang et al 2017; Chen and Chang 2018; Kim 2019; Lee et al 2020) For example, A study based on travel planning behavioral theory has demonstrated that perceived value (positive attitudes, subjective norm, economic benefits and unique accommodation) have a positive effect on the RI of Airbnb while perceived risks are contradictory (Amaro et al 2018) Meanwhile, Jun (2020) discover that there is a positive relationship between brand credibility and past experience with RI, which is negatively

as well as the enormous impact covid-19 has brought show the close link between the values that customers recognize at Airbnb and the risks it can affect to this company Therefore, the interaction between value and risk seems to be important in terms of predicting RI in this unstable context In order to enrich the existing literature, as well as examining the factors that can affect the current PR, this research combines PV of customers who use airbnb before and the risk that they perceived from covid-19 pandemic

2.4 Perceived value

Perceived value for a long time has been known for the important role in term of understanding customer's repurchase intention (Wang and Jeong 2018) The most common definition of perceived value was cited from Zeithaml (1988, p 14) which refer to “the consumer's overall assessment of the utility of a product based on perceptions of what is received and what is given” Whereas, Kashyap and Bojanic (2000) posit that all definitions of perceived value typically involve to some form of trade-off between what the consumer receives (utility, quality, benefits) and what he or she gives up to acquire and use a product (price, time, effort, sacrifice) This study adopts the views of Sweeney and Soutar (2001), defining perceived value as the consumers’ overall assessment of the net values (benefits) of booking accommodations via Airbnb and their perceived value

The relationship between PV and RI has been studied and confirmed in consumer behaviour research (Grewal et al 1998; Kuo et al 2009) Indeed, consumer's value is the fundamental basis for all exchange activities (Holbrook, 1994) and can drive buying choice (Neal 1999) It was found that higher PV would lead to a willingness to pay (Dodds et al 1991) In addition, within the repurchasing behaviour studies, PV was found to positively influence consumers’ RI (Chiu et al 2012; Wu et al 2014) For example, Liang et al (2017) found that antecedent of

PV such as price sensitivity, perceived authenticity, and electronic word-of-mouth positive impact RI Whereas Stollery and Jun (2017) show that monetary saving, hedonic benefit and novelty increase PV which lead to higher intention to continuing stay in Airbnb

Following the suggestion that perceived value is context-dependent, the specific antecedents examined in this study are based on exiting literature associated with the use of Airbnb

including website useage (ease of use, effectiness) and home benefits (amenities, host-guest

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interaction, PA and novelty) (Carlson Wagonlit Travel 2015; Folger 2016; Guttentag 2017;

Tussyadiah and Pesonen 2016)

2.4.1 Perceived usefulness

According to (Davis et al 1989), perceived usefulness refers to consumers’ assessment in regard to the experience's outcome

Likewise, (Mathwick et al 2002) defined perceived usefulness as the individual’s perception

of whether adopting a particular system will boost his or her performance This factor has been recognized as an especially important indicator of customers' perceptions of value for new

technologies (Bruner and Kumar 2005; Taylor and Todd 1995), which is Airbnb particularly

Taking a more practical approach, for example, Wang and Jeong (2018) surveyed Airbnb users

in the United State, and revealed that Airbnb repurchase was crucially influenced by the attitude which is initially based on perceived usefulness from the Airbnb website Similarly, Amaro et

al (2017) also state that usefulness is an important element for measuring users’ intention toward Airbnb These findings demonstrate perceived usefulness's role in the sharing economy context

2.4.2 Economic benefits

Economic factor has been broadly identified as a key factor that affects consumers’ behaviour (Roma et al 2019; Dogru et al 2020) The economic benefits are usually appealing as one of the fundamental advantages of participating in the sharing economy (e.g Airbnb) (Tussyadiah

& Pesonen, 2015) In fact, the Airbnb business model financially benefits for both party take park in the platform Admittedly, the reason Airbnb considered as an economical option is because Airbnb not only offers more affordable price than hotels for tourist, but also the host can generate a promising income when offer their available space for other people (Karlsson and Dolnicar 2016)

2.4.3 Household benefits

Guttentag (2016) suggests that household amenities and location are functional factors that contribute to the perceived value of Airbnb With regard to household amenities, it mainly refers to the basic home offerings such as kitchenware, in-home washer and dryer, fridge) and other appliances that are present at an Airbnb property Airbnb amenities are somewhat different from those offered by traditional hotels (e.g., 24/7 staff availability, check-in/out

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process, attached restaurant, fitness facilities, and business centres) because Airbnb customers expect to have similar amenities to those they have at home In addition, there are more than 85% of guest consider amenities when looking for Airbnb accommodation (Wang and Jeong 2018) In term of location, Tussyadiah and Zach (2015) confirmed that location was significant for both hotels and peer-to-peer short-term rental, even though hotel customers reviews wanted

to search for a convenient location while sharing guests tended to focus on a desirable location

in general Yang and Mao (2020) also unveil that location advantage (accessibility to points of interest, transport convenience, the surrounding environment, and market conditions) enhances property performance which leads to higher PV

Although the existing literature has emphasized various advantages that the household amenities as well as location benefits (Guttentag 2015; Quinby and Gasdia 2014), limit research has empirically investigated the connection between customers’ attitudes toward these functional factors and customer perceived value with staying at an Airbnb house Both Bellotti

et al (2015) and Yu et al 2020) have highlighted the value of amenities in an Airbnb and classified this factor as the key elements that drive guests’ value perception with their stay experience

2.4.4 Host guest relationship

As Airbnb is a form of “sharing” services, the host-guest interaction cannot be overlooked during the entire process from customers’ information search to transaction completion or even

to their departure Consumers’ behavior changes once the HGR is established (Lampinen and Cheshire 2016)

Theoretically, Airbnb features value co-creation, which is an economic exchange process that helps all parties involved in creating shared values (Vargo et al., 2008) On the one hand, each guest-host relationship is created by the quality of service provided by the host Dimmock (2012) believes that customers buy a product and service not only because of the physical value but also because of the experience that the seller offers Indeed, in the past when social networks were still underdeveloped, information was scarce, standardized features at hotels were the standard travellers used to judge quality, however, thanks to the explosion of technology, other standards are gradually formed Online consumer reviews, for example, can reduce concerns about unpleasant travel bookings and increase the need for more special experiences (Maney 2014) Another example is the desire for authentic experiences from local community which represents an important driver in Airbnb's selection, which openly presents itself as a provider

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of such experiences (Yannopoulou et al 2013) On the other hand, the role of hosts who can share local tips and provide travel advice to Airbnb users is recognised (Tussyadiah and Pesonen 2016), and an enhanced connection with the service provider is achieved by engaged customers Therefore, the co-creation process significantly affects consumers’ satisfaction and consequent behaviour is repeat purchase intention (Finster and Kuppel 2011)

According to Guttentag (2016) both hosts and guests are consumers in the Airbnb context and HGR determines their willingness to contribute to both parties’ experience Out of the 5 types

of people looking for short term accommodation including Money Savers, Home Seekers, Collaborative Consumers, Pragmatic Novelty Seekers, and Interactive Novelty Seekers (Guttentag 2015), there are three types of guests (collaborative consumers, pragmatic novelty seekers, and interactive novelty seekers) who are motivated to use Airbnb because of the chance

to interact with their hosts and other locals Kim et al (2015) also indicate that if Airbnb guests feel that they have solid and close relationships with their hosts, they become more satisfied with their overall Airbnb experience than guests with no interactions with their hosts

2.4.5 Perceived Authenticity

Since introduced by MacCannell’s in 1973, the notion of perceived authenticity has been widely examined in tourism research (Chhabra et al 2003; Ramkissoon and Uysal 2011) Previous studies on Airbnb authenticity recommended that tourists who seeking local lifestyle may see Airbnb attracted and prefer this sharing accommodation rather than hotels (Yannopoulou et al 2013; Guttentag 2013) In addition, perceived authenticity proved that positively and vitally affected the cultural behavioural intentions of tourists on the island of Mauritius (Ramkissoon and Uysal 2011) Couchsurfing and Airbnb have also claimed authenticity as it's brand characteristic (Yannopoulou et al., 2013) In term of catering, Lunardo and Guerinet (2007) noticed that perceived authenticity influences the buying behaviours of millennial buyers in wine consumption Regarding home-sharing services research conducted by Tussyadiah and Pesonen (2015), discovered that tourists’ desire for interactions with locals and authentic experiences positive result in their travelling behaviour

2.5 Perceived risk

Travel risk is defined as the possibility of experiencing danger while travelling (Mazri 2017)

or the consciousness of insecurity and knowledge of the likelihood of damage while travelling (Wogalter et al 1999; Park and Reisinger 2010) Park et al (2016) defined it as a consumer’s belief about the potential uncertainty associated with negative outcomes in a purchase situation

Many studies have shown that the higher the perceived risk, the lower the intention to buy back (Vijayasarathy and Jones 2000; Wu and Chang 2007; An et al 2010) Wu and Chang pointed out that the risk attitude directly affects the intention to buy online, the researchers mentioned four types of risk that have a great impact are natural disaster risk, physical risk, risk political and operational risks Regarding, natural disaster risk, it is assessed as having the greatest impact on travel intention The argument that tourists consider disaster risks as threats that directly affect tourism intent is also supported by research by An et al (2010) Similarly, Chiu

et al (2014) also determined that PR is negatively related to RI In most studies involving consumer behaviour on the relationship between PR and PV, PR is considered a precursor to

PV (Horton 1976; Sweeney et al 1999; Kim et al 2008; Chang and Tseng 2015) Summarily, while PV is positively related to RI, PR is the premise that negatively affects RI In this study, risk represents as a moderator, implying that purchasers will weigh both benefits and risks when assessing the value of a product or service and from that point of view forming buying intentions (Chiu et al 2014)

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2.5.1 Perceived risk in a crisis (Covid-19 pandemic)

The novel coronavirus which is popular short for COVID-19 pandemic has had a significant impact on tourism industry due to the widespread introduction of travel restrictions by states as well as massive and unprecedented slump in demand among travellers (Gössling et al 2020; Hall et al 2020) Tourism is considered as one of the hardest hits by the COVID-19 outbreak, with millions of jobs at risk in this labour-intensive sector of the economy (UNWTO 2020) According to the UNWTO’s forecasts, international tourists would be decreased by 60% to 80% in 2020 which may affect 100–120 million direct tourism jobs at risk (UNWTO 2020) The COVID-19 crisis and the ensuing social distancing has significantly disrupted the tourism industry and wider economy including the sharing economy services While P2P accommodations and more particularly Airbnb were at a constant growth prior to the COVID19 outbreak, this pandemic has shaken up the whole sector (Watson 2020), and demand for short-term rentals has witnessed significant setbacks (DuBois 2020) For instance, Airbnb’s revenue

is expected to be less than half of what it was in 2019 (Khan 2020)

While, the flexibility of amenities that Airbnb offers (e.g room space, pet-friendly, family friendly, and various entertainment amenities) and its provision of home-based amenities, was

a challenge to common practices in the traditional hotel accommodation sector (Yu et al 2020),

in the current COVID-19 travel environment, it is argued that potential travellers’ consumption patterns will be affected (Wen et al 2020), less travellers would use P2P accommodations services and travellers are less likely to choose Airbnb listings (Wood 2020) However, Dolnicar and Zare (2020) claim that by the proper control of this pandemic, demand for P2P accommodation would keep growing quickly More recently, P2P accommodations have developed cleaning protocols for hosts (e.g 24-hour vacancies between bookings in Airbnb) in

an effort to address the ongoing challenges and pressure created by the virus and to limit possible coronavirus transmissions (Wood 2020) This highlights the importance of cleanliness and hygiene as significant factors in P2P rental sector’ attraction in COVID-19 times (Chadwick 2020; Naumov et al 2020; Wen et al 2020) Given the inherent uncertainties surrounding COVID-19 and its impact on the booking behaviour of travellers, the future of the global short-term rental market is hard to predict (Gössling et al 2020) For instance, recent global survey series conducted by McKinsey & Company (2020) across 42 countries on the consumer sentiment and behaviour during the COVID-19 crisis show that consumer sentiment

is evolving in coronavirus crisis and there is a greater emphasis on enhanced cleaning practices and sanitation measures (McKinsey and Company 2020) For instance, empirical study of

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Naumov et al (2020) shows that Bulgarian tourists do not generally trust the cleanliness and sanitation protocols at P2P accommodations and prefer family-owned apartments and second homes for the best hygiene and sanitation comfort As the lockdown restrictions in several countries are eased, consumers’ demand for higher level of cleaning standards and sanitation is particularly significant for P2P rental sector which requires restoring customer trust (Chadwick 2020; Gössling et al 2020; Naumov et al 2020)

2.6 Hypothesis

Based on the exiting literature, the hypotheses relating to PV, PR, and RI were proposed as follows:

H1: Economic benefit positively related to Vietnamese customer PV

H2: Perceived usefulness of Airbnb website positively related to Vietnamese customers’ PV H3: Home benefit positively related to Vietnamese customers’ PV

H4: Host-Guest relationship positively related to Vietnamese customers’ PV

H5: Perceived authenticity positively related to Vietnamese customers’ PV

H6: COVID-19 is positively related to Vietnamese customers’ PR

H7: PV positively related to RI

H8: PR negatively related to RI

Figure 2.1: Model conceptual

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2.7 Research gaps

The literature review is considered as a tool of the researcher to collect secondary data which server for the further research analysis, however, there is still many gaps in the resources, particularly in Vietnam sharing economy market Firstly, the available resources for secondary data linking to Airbnb market in Vietnam are extremely poor since only a few publish article specially examined this sector Secondly, there is currently no research particularly on repurchase intention in Viet Nam Lastly, there is fairly limited research related to Covid-19 pandemic in general and it is even more limited number of the research about the effect of Covid-19 on sharing economy

The main purpose of this study is to “explore and identify the factors that influence Vietnamese travellers’ Airbnb repurchase intention in the post-pandemic (COVID-19) context.”

Thus, there is a need to achieve aim and objectives which are listed as below:

1 To investigate the relationship between past experience, current situation and future repurchase intention of Airbnb customers

2 To examine the impact of economic benefit, usefulness website, home benefit, guest relationship and authenticity on perceived value

host-3 To test the impacts of the Covid-19 pandemic in Vietnamese travellers’ Airbnb perceived risk, hence, turn into repurchase intention

3.2 Research Philosophies

According to Kothari (2006, p 8), the research method is defined as “a way to systematically solve the research problems; in other words, it is a science of studying of how research is done scientifically” The purpose of conducting research is to enhance knowledge that people desire, they undertake it in a systematic way to test the hypothesis which is proposed (Saunders et al 2009)

Research philosophy refers to the approach to a research topic for the purpose of developing knowledge during the research (Saunders et al 2000) According to Saunders et al (2007), research philosophy is divided into two main categories: First, positivistic philosophy, observing social reality based on its true nature, then based on the collected data to make analyzes for the theories Second, phenomenological philosophy, observing social reality as it complicated to study Specifically, the difference between two philosophy is illustrated in the below table:

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Figure 3.1: The Comparison between Positivistic Philosophy and Phenomenology

(Amended from Collis and Hussey (2003)

As displayed in Figure 3.1, the research philosophy is adapted for this research is the positivistic approach because this research requiring a quantifiable analyses method to gather primary data

3.3 Research Approach

As a researcher, it is important to understand a research approach, only when clearly understanding the relevant theories and the differences between approaches, the researcher will then know how to design a project There are two research approaches methods consists of deductive and inductive (Trochim 2006) Inductive research is an approach where collected data is used to develop a general theory or idea In contrast, a deductive approach uses general theories or ideals to confirm a particular assertion (Cooper và Schindler 2006) For this study, the deductive approach is employed The reason is that the research has available literature collected in chapter 2, combined with primary data collected from the questionnaire to examine the original research purpose

3.4 Secondary research

Secondary research is known as the direction in which the researcher collects available data, which can be either raw or fully published data (Zikmund et al 2010) Secondary data are also known as literature review, this type of data could be books, scientific papers, journal articles

or other mainstream sources of information (Blaxter et al 2010; Blumberg et al 2005) Secondary research is seldom a complete research paper but mostly a summary or synthesis of data with the goal of aggregating data for primary research (Crouch and Housden 2003) (Jennings 2001) posit that the researcher to could avoid unnecessary missing the concept of the research when reviewing onto literature Moreover, it is comparatively easier and faster and consequently saver In addition, Hart (2000) suggest that there are several channels and ways

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to collect secondary data including textbooks, online resource journals and articles etc In this research paper, secondary research plays an important role in the process of collecting data related to the topic Most of the research information noted in Chapter 2 comes from online resources including books, textbooks, newspapers, reports and other official sources gathered via the internet, especially the majority reference is gathered from e-resources such as at Google, Google scholar and Bournemouth University Library (Sharp et al 2002) In fact, the importance and convenience of the internet are undeniable, thanks to the online engine that researchers can gather enough information for the essay despite the pandemic period Notwithstanding, it is essential to seriously reference reliability and validity of sources when collecting secondary data as there are always unauthenticated sources often available online (Jennings 2001)

3.5 Primary research

Primary research refers to new data which is directly collected by observing Veal (2018) suggests that researchers can collect primary data by doing interviews, questionnaire surveys, observations, or experiments in which the collected data will be used for the first time in the data collector's research paper In other words, when collecting secondary data, when the researcher did not find enough data required to conclude the answer for the purpose of the study,

a primary study needs to be performed (Clark et al 1997) Primary research is a time consuming and costly method (Baggio and Klobas 2011) On top of that, it involves human participation, which means that the research can have a positive/negative affect on their emotion or violate participants privacy or even related to some of the moral values (Jennings 2001) However, the benefits of primary research are numerous Firstly, primary research allows researchers to reach the right sample audience they are targeting for research purposes (Ghauri and Gronhaug 2010) After that, the collected data source can be used, studied, analyzed specifically according to the research intent (Jennings 2001) Last but not least, Data are immediately updated, recent and closely relevant to each other according to the goals of the project designer This helps the researcher to avoid using unnecessary error methods (ibid) In addition, only primary studies are able to obtain data regarding customer's behaviour, intention and attitude (Ghauri and Kjell 2010) There is a total of three methods to carry out a primary data collect project: qualitative method quantitative method, and mixed-method of qualitative method and quantitative method (Jennings 2001) The two common methods are qualitative and quantitative

In this research, Veal method is chosen to perform research objective analysis, using a questionnaire to collect response data Although Veal (1997) has criticized the questionnaire

To obtain reliable results, it is essential when collecting data that the number of samples is sufficiently large (Veal 1997) As mentioned, this study chose to conduct quantitative research using the survey questionnaire This method is found to be suitable for the researcher to understand and discover the factors involved in a customer's intention to stay at Airbnb after the post-pandemic period Participants in the above study use electronic devices to fill out the survey via the internet This is a self-filled questionnaire, the participant takes 3 to 5 minute to complete and the result will then automate sent to researcher data collection system

3.6 Questionnaire design

Questionnaire survey, as the most popular approach to quantitative research, is defined by De Vaus (2002) as a general term for all data collection techniques When participating in a survey, the same questionnaire was distributed to the participants and they would answer in the same predetermined order This is the most effective method to collect a large number of samples in

an acceptable time or can be said to be short if compared with the interview method (Finn et al 2006)

Questionnaire design is a very important step in the research process The quality questionnaire was the deciding factor for whether the collected data met the standard of analysis and was suitable to account for the original research objectives In addition, according to Brace (2013), when designing the questionnaire, the designer must carefully approach to avoid bias as much

as possible Furthermore, a good questionnaire can save costs, time, resources and space, which will benefit research in many ways (Wallen and Fraenkel 2011) Moreover, the response rate can be increased if the questionnaire has a good presentation, a medium length and clear questions (Wallen and Fraenkel 2011)

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There are two types of questions in the questionnaire, closed questions and open questions For closed questions, this is a question in which the participant is chosen to answer between the available answers and the answer simply short and clear such as yes or no An example can be seen in Appendix 1, question number 2 is a closed question with two options of Yes or No Another closed question type is a multiple-choice question where the participant allowed to choose more than 1 answer to the same question (Veal 1997) This type of question can be seen

in question number 4 and 5 in Appendix 1 when design this type of question, the researcher needs to base on literature review and current fact, however, these can lose spontaneity in answers (Oppenheim 2009) Therefore, for a question that allows answers to be extended, the designer can add "other" option in the answer box

Open questions are questions that allow respondents to give their answers, freely expressing their opinions and ideas (Oppenheim 2009) However, many studies have recommended that open questions should be avoided in questionnaires as respondents can leave them blank and not write answers in questionnaires In addition to the problem of lack of answer structure, Veal (1997) also claimed that open questions were difficult to examine and compare between groups

of answers Therefore, this type of question should be restrained in the survey The completed questionnaire for this study was constructed by creating an online form in the JISC system which is a data collection website The researcher chose the JISC system for the fact that it is widely use, free and easy to access For this research, the English version was initially created before being translated into Vietnamese to accommodate Vietnamese participants

self-The questionnaire was divided into three sections which included 18 main questions In Section

1, from questions 1 to 5, concerns respondents’ general data regarding Airbnb past experiences The first section collects the participation’s information about staying in Airbnb; therefore, close question with single answer and multiple-choice questions are asked about past experience of customer

The second second, from question 6 to 11, is the main part of the questionnaire, which is about the factors may affect the AirbnbRI This section comprises of 27 sub-questions using a five-point Likert-type scale (1=Strongly Disagree, 2=Disagree, 3=Neither, 4=Agree, 5=Strongly Agree), in which a new structure modified and adopted from perious reserch The Covid-19 related questions also use a five-point Likert scale, asking directly about attendees’ intention

on repurchase an Airbnb in the future base on their original intention before the pandemics and their risk perception according to the pandemic For a more overview, the academic sourse for questionnaire was also list on Table 3.2

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6 Economic

benefit

E1 I could save money when I book accommodations

from local hosts on Airbnb

Kim et

al

(2008) E2 I stay at Airbnb for a better place with less money

7 Usefulness U1 Airbnb website is understandable (Wang

and Jeong 2018)

U2 Information about the property is fully provided) U3 Convenient to find a suitable accommodation

8 Home benefit H1 Airbnb allows me to use amenities and facilities

which hotel does not have

(Amaro

et al 2018) H2 The Airbnb provides me with what I need as expected

9 Host-Guest

relationship

and Jeong 2018)

HG2 The host is helpful HG3 I like to interact with the host as way to connect with

local cuture

10 Authenticity A1 Living in an Airbnb place allows me to experience an

authentic local lifestyle

Liang et

al

(2017) A2 Living in an Airbnb place allows me to live as a

resident A3 Living in an Airbnb place allows me to interacted

with the local community

11 Covid-19 C1 Covid-19 affects my budget for my future

C2 Covid-19 affects my intention to stay with Airbnb

C3 Covid-19 affects the frequency of my stay with

Airbnb

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C4 I will stay in an apartment / private room instead of

sharing an apartment / room with the owner for health reasons

11 Perceived

value

PV1 I find using the Airbnb website is a good idea (Liang

et al 2017)

PV2 I find staying at Airbnb is worth the money PV3 Living in an Airbnb place would help me make more

local culture experience PV4 Overall, I enjoy living in Airbnb

Airbnb place/listing PR3 I am concerned about the cleanliness and sanitation

protocols at Airbnb PR4 I am concern that I may not financial stable to stay at

Table 3.1: Questionnaire design

Finally, the third section, questions 12-15, includes respondents' personal data relating to demographic factors such as age, gender, education level, and income level The purpose of these questions is to test whether there is a difference in intention to continue buying among demographic-related variables

According to Kotler et al (2010), personal characteristics (age, values, occupation and economic circumstances) can influence the buying behaviour of customers Besides, Richards and Wilson (2003) emphasize that gender difference also affects product preference and interest

in products

3.7 Sampling and sample size

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3.7.1 Sampling

Besides designing a good questionnaire, sampling also has an important influence on the quality

of analysis results Sampling is a technique of selecting a group of people to be a representative

to answer the questions in research (Walliman 2006) This group can be considered as a sample

of the study, representing the entire population for which the study unable to collect data from According to Clark et al (1998), there are two basic types of sampling techniques: probabilistic sampling (random) and non-probabilistic sampling (non-random) Probability sampling technique means that respondents will be selected randomly while non-probability techniques will be selected depending on the number of samples according to the researcher preference

In this study, the probability sampling technique was chosen to distribute the online questionnaire survey, as this was an appropriate technique for this study to gather data by random selection from those Vietnamese travellers aged from 18 and above which have made

a reservation through Airbnb website at least once Figure 3.2 lists some main sampling measures under each type of sampling technique

Figure 3.2: Sampling technique (Israel 1992)

3.7.2 Sample size

The research population target in this study is all Vietnamese participants over the age of 18 who have stayed in Airbnb before According to Baggio and Klobas (2011) selecting an appropriate sample is significant If the sample is too large it may cost time and money, while

a small sample may lead to inaccurate results (Clark et al 1998) Due to the large population and the researcher does not know the variability in the proportion of Vietnamese joined in the

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survey, the Cochran formula suggested by Israel (1992) is adopted The equation is displayed

in Figure 3.3

Figure 3.3: Sample size equation (Israel 1992)

This formula uses an equation consisting of a Z score which is the abscissa of the normal curve that cuts off an area α at the tails, the desired level of precision (e) and the estimated proportion

of an attribute that is present in the population (p) to calculate the corresponding sample size

It assumed that the Z-score is 1.44 when the confidence level is set at 85% (Weebly 2019), p= 0.5, q= 1-p and e= +/-0 5% (Israel 1992) Following the equation, the sample size is 208 The number of survey samples expanded to 220 to eliminate unsatisfactory surveys

3.8 Pilot test

A pilot test is an act of testing to determine whether the questionnaire is reliable or not before launching the survey on a larger scale (Finn et al 2000; Saunders et al 2009) The purpose of this empirical test is to minimise the potential issues which may occur during the data collection process as well as reveal any hitches or difficulties when respondents answer the survey (Bell 2010) Bell (2005) also posits that this test allows the researchers to check thư time to fulfil the questionnaire of respondents and receive reviews from them about whether all instruction and questions are understandable and all data is useful The suggested number of participants in a pilot test is 10, therefore, 10 known students who have previously stayed at Airbnb are invited

to join this experiment Some change about the presentation, language translations, and the number of questions is ament before initialling distribute the survey to the public

Z= the abscissa of the normal curve that cuts off an area α at the tails (e.g 1.44 for 85% confidence level) e= the desired level of precision

p= the estimated proportion of an attribute that is present in the population

q= 1-p

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3.9 Data analysis

After reaching the target sample size, the collected data was exported from the JISC survey system to SPSS 26, which is short for Statistical Package for the Social Sciences version 26, to analyse the result This software is known as the most frequently used tool for sorting, arranging and analysing data in various quantitative researches (Moore 2006) In addition, due to the complicate characteristic of the conceptual model (finger 1), this study also employed the Analysis of Moment Structures (AMOS) to achieve an accurate result and improve the outcome (Bryman and Cramer 2005; Brown et al 2009) In order to analyse the data, the researcher used techniques including Descriptive Analysis, Factor Analysis, Correlation Analysis, and Linear Regression

Firstly, this research utilised Descriptive statistics to analyse personal and demographic information which can be found in the first and last section of the survey Through these questions, respondents reveal the basic data characteristics as well as compare and output the Airbnb's usage frequency distribution (Brotherton 2008) Secondly, Factor Analysis consists of reliability and validity analyses examine whether the result is valid and rationale for further analysis or not The Confirmatory Factor Analysis (CFA) was adopted for this measurement Furthermore, The Correlation Analysis is conducted in order to measure the meaningful and significant of the relationship among each element in the conceptual model Then the Linear Regression Analyses are used to measure the links in the relationship between past experience and post-pandemic situation with the repurchase intention The main purpose is to discover the key factors in Airbnb experience that determine customer’ repurchase intention

3.10 Conclusion

In conclusion, this chapter showed all the research methodologies adopted for this study These are the research approach, questionnaire design, sampling and sample size, pilot test, and data analysis process In addition to the employed techniques, the chapter also highlights the limitation to show a complete picture of the research process In the next chapter, the finding and discussion of the research will be presented

4.2 Descriptive Analysis

4.2.1 Demographic characteristic

This study collected an effective sample with a sample size of 238 According to Table 4.1, which is the Demographic characteristic analysis, 45.4% of the respondents are male and 52.2% are female 47.1% of the respondents are aged between 18 and 24 years old, 40.3% from 25 to

35 years old, 9,2% from 36 to 45 years old and the number of respondents above 46 years old

is 3.4% In the education level category, participants holding bachelor degrees and above is dominated the sample size with 89.5% out of total Participants with high school degree is 8.8% and 1.7% end their education at middle school or under level At the income level, 119 account for 50% of respondents earn average national level, which is consider at between 6 to 15 million VND per month according to Statista (2020), 39.1% make more than 15 million and 10.9% earn under 6 million per month