The Rise of Airbnb in the Sharing Economy

1.0 Introduction

1.1 Background

Belk (2014) points out that sharing economy is the sharing of consumption using online platforms. This became much popular since the beginning of the 21st century and up to date, it has expanded to the travel industry (Sthapit, 2019). A study conducted by Ozan (2018) discovered that the number of people who use the sharing economy have increased by 60% for the past 18 months in the UK. In addition to this finding, it is evident that Warwick Business School as well made a discovery that 23% of the population in the UK utilizes the services of sharing economy for a number of times every month. In this case, the more qualified an individual is, the more likely he or she is able to utilize platforms like Airbnb and Uber (Ozcan, 2018). Of importance to this dissertation is Airbnb, which is a perfect example of sharing economy. Notably, it is world’s biggest provider in the sharing economy, in terms of lodging (Mody et al., 2019). In 2008, Brian Chesky, Nate Blecharczyk, as well as Joe Gebbia established Airbnb. Moreover, of importance to note is the fact that Joe and Brian came up with the first Airbnb accommodation apartment in San Francisco (Airbnb, 2019).

Lu et al. (2019) point out that as an online platform, Airbnb permits people to lease accommodation, thereby, allowing buyers to have a reservation. According to Guttentag (2015), these accommodations could be an entire space such as a house or an apartment or an independent room, which is an accommodation alongside the host. Airbnb has a variety of properties consisting of alluring accommodations such as igloos, chateaus among others. Moreover, Sthapit (2019) notes that it has its listings, which range from budget to greatly indulgent. According to Gurran et al. (2017), in order for people to book an accommodation reservation using Airbnb, the entire process is similar to utilizing online travel agency and as such, it may be necessary for the traveler to establish a connection with the host. Guttentag (2015) state that Airbnb’s expansion is affecting certain conventional tourism accommodations, owing to the fact that it converts a larger proportion of the population into engaging with the hospitality micro-entrepreneurs, thereby, creating tourism lodgings whilst creating critical policy concerns globally. Since time immemorial, Airbnb has purposed to expand its operations worldwide to approximately 191 countries and in 100,000 cities. Additionally, it has over 6 million listings globally (Airbnb, 2019).

The hosts that are utilizing the Airbnb in the UK are millennials, couples, and senior citizens. In this regard, the mean age for the hosts in the UK Airbnb is 44, and whilst considering this, 61 per cent of them are females, whereas the remaining 39 per cent are males (Airbnb, 2018). Notably, Airbnb in the UK provides a flexible income source, owing to the fact that most of the hosts make averagely £3100 annually. Essentially, this can supplement the income of some individuals who work full-time. It can also assist in securing income, especially for self-employed hosts, and as well offer a way that retirees can utilise in earing extra revenue. Additionally, in accordance with the writings in Airbnb (2018), Airbnb benefits approximately 3 per cent of hosts, owing to the fact that this platform aids them in countering foreclosure or expulsing as it offers a dependable source of income. Guibourg et al. (2019) indicates that the number of rooms accessible for reservations in Airbnb, in the UK have increased in most of the cities. For instance, BBC data indicates that the Airbnb listings doubled in Edinburgh city, for the last 3 years, and also doubled and quadrupled in London city since 2015, from 20,000 listings to 80,000 listings. In line with this, it is evident that there are about 80,000 listings in London city, which are more as compared to any other UK city. In terms of costs, Lu et al. (2019) notes that individual reservations of a room using Airbnb is same to booking a reservation in medium-tier hotel. Additionally, Oskam et al. (2016) note that the prices of Airbnb are noted to be competitive due to the fixed costs, as well as utilities of the hosts, which collectively have low expenses, and also additional income that are attained through rentals. Furthermore, its guests revel, especially in local experiences like communication with the hosts, and neighbours (Guttentag, 2019). For instance, Nguyen (2014) in his writings provided a perfect example, whereby a CEO of one of the major tour operators made an allegation that tourists were ambitious when it came to having local experiences, and due to that Airbnb instantly came up with a marketing logo, which stated, “Belong Anywhere” in order to attract more travellers.

Essentially, hotels pose as Airbnb’s greatest competitors, owing to the fact that they also offer short-term accommodation services to travellers (Guttentag, 2015). In this regard, this dissertation will focus primarily on the two platforms. The routines of hotelier and Airbnb are extremely contrasting, particularly in the manner in which they operate. A hotel operator is bound to strictly follow set rules, correlate fire code, ensure licensing, and even adhere to employment standards (Liang, 2015). On the other hand, Airbnb hosts have a lot of freedom, as they have a lot of space in their dealings (Van et al., 2015). Notably, Fromm (2019) states that millennials are also contrasting when they are compared to other generations, as they have distinctive expectations for various brands. Fromm (2019) goes further and explain that millennials do not plan and book their travels in advance, rather, they purpose to make their travels in a rush, in few days or weekends earlier. Various factors attribute to this, and in this regard, social media poses as the major cause, whereby, millennials observe their treasured influencers or friends uploading photos, as well as videos of different locations that they visit. As such, their craving to visit different places is continually tested (Brown, 2019). Fromm (2019) note that they prefer travelling by airlines that are low-priced, thus, implying that they are averse with higher transport costs, yet in an instance where the air fare is cheaper it is notable that they are most likely to travel. It is evident that Airbnb offers a cheaper option for many millennials that seek accommodation wherever they are travelling, and it also provides various possibilities plus more interaction with various locals (Brown, 2019). As such, is worth noting that millennials play a vital role in the gradual, yet constant changes in the traditional travel accommodations towards the provision of innovative spaces that are similar to those that are offered in the Airbnb platform. Notably, this trend shifts from hotels, owing to the fact that the young generation prefers reservations through vocational rental services like Airbnb. As such, this dissertations will look at millennials in relation to hotels and Airbnb.

1.2 Aim

Sharing economy is noted to affect the entire global economy, as it involves an increasing scale, owing to the fact that customers are able to exchange their commodities in a way that is more organized with the help of online platforms (Guibourg & Peachey, 2019). In the holiday accommodation context, it is evident that the growth of Airbnb has over the years been stunning, owing to the fact that it has more available rooms, as compared to most hotel giants. Factually, research has been able to highlight the potential of Airbnb in disrupting the sector of traditional accommodation (Gurran & Phibbs, 2017). Given the significance of Airbnb, it is of vital importance for this dissertation to examine various factors, which affect intentions towards booking an accommodation on Airbnb in comparison to hotels. Notably, perceived usefulness was noted to positively influence millennial’s attitude towards Airbnb (Guttentag, 2015). Looking deep into this issue, it is noteworthy that what really matters to book on Airbnb than on hotels are various motivation factors, as they pose as the strongest predictors on booking on Airbnb. According to Guttentag (2019), one of the motivation factors that this dissertation will focus on will be on the financial aspect, as Airbnb provides quality accommodation, with low prices as compared to hotels. Notably, this is more vital to millennials who are becoming used to accessing more things than they could ever own (Lu et al., 2019). Secondly, the most significant predictor of motivation towards booking on Airbnb than hotels is subjective norm. Essentially, the attitude among millennials towards online shopping as well affects motivation to book on Airbnb than hotels (Nguyen, 2014). Overall, these motivation factors indicate that millennials in the UK prefer Airbnb to staying in hotels. As such, the aims of this research are as presented below:

To discover the motivations of millennials in the UK towards Airbnb

To provide reasons why millennials in the UK prefer Airbnb to hotels

1.3 Objectives

In a bid to meeting the aforementioned aims, this study, will pursue the following objectives:

To find out the motivations that millennials in the UK have towards Airbnb

To investigate the reasons why millennials in the UK prefer Airbnb to hotels

To determine the advantages that Airbnb has over hotels

1.4 Research questions

Similarly, meeting the above research objectives will mean answering the following research questions:

What are the motivations of millennials in the UK towards Airbnb?

What are the reasons why millennials in the UK prefer Airbnb to hotels?

What are the advantages that Airbnb has over hotels?

2.0 Literature review

2.1 Introduction

Even though in the past years Airbnb has become popular amongst travelers (consumers), it is noteworthy that the existing quantitative research on the link between Airbnb and the buying behavior of consumers is inadequate (Liang, 2015). Most studies concentrate on the components of Airbnb that make it successful in the hospitality industry and this includes company regulation, monetary considerations, urban planning, as well as potential discrimination (Guttentag, 2015; Zervas et al., 2015; Koopman et al., 2015; Gurran et al., 2017; Edelman et al., 2014). Additionally, scholars such as Brochado et al. (2017) provide the importance of individual preferences, which affect buying decisions whilst relating it to Airbnb that pose the need for them to be examined in the forthcoming studies. Notably, preceding studies concentrate much on the impacts of Airbnb on consumer behavior globally, and on this note, it is evident that not even one research focuses on comparing hotels in the UK with Airbnb (Zervas et al., 2015). In this regard, it is of importance for this study to examine the effects of Airbnb on the UK hotel Industry. This chapter is arranged into significant, yet distinct themes as provided in the research objectives.

2.2 Attitude

Attitude poses as a major behavior determinant, owing to the fact that the intentions to perform certain behaviors can easily be predicted with high accuracy based on the attitude towards the given behavior (Soomro & Shah, 2015). Empirical studies indicate that various motivational factors assume powerful predictive role, especially in explaining attitude, which subsequently explains behavioral intentions. Over the years, consumer researchers have become much concerned with comprehending the connection between attitudes, and subsequent behaviors (Yoo et al., 2016). Essentially, Ladhari & Michaud (2015) point out that attitude is centrally positioned when it comes to researching on consumer behavior. In this regard, various studies highlight that general attitudes, as well as personality traits often predict behavioral aggregates more than as they are able to predict particular behaviors (Haugtvedt et al., 2018). In accordance with the theory of planned behavior, Montano & Kasprzyk (2015) state that intention and action are influenced by an individual’s past-experience partially, and can as well be influenced by second hand information, both from friends or acquaintances, and by certain factors, which either increase or reduce perceived difficulty of behavior performance.

2.3 Theory of planned behavior

Theory of Planned Behavior (TPB) was developed with the aim of predicting a person’s behavioral intention within a context. According to this theory, behavioral intention indicates a person’s willingness to behave in a particular way (Montano & Kasprzyk, 2015). Moreover, this theory points out that a person’s behavioral intention can be directly influenced by various motivational factors in their decision-making process. Kautonen et al. (2015) notes that TPB has been applicable in the tourism and hospitality research, to explain and comprehend traveler’s behavioral intentions. For instance, it has been used in studying traveler’s intentions of staying at green hotels. Moreover, other scholars such Paul et al. (2016) use this theory in directly studying and examining various factors that influence consumer’s attitude towards Airbnb context intentions. According to So et al. (2018), they note that TPB was perceived as relevant to guiding conceptual framework and to studying the motivations of Airbnb consumers. The following figure illustrates the Theory of Planned Behavior

2.4 Innovation Diffusion Theory

Innovation Diffusion Theory (IDT) is similar to innovation adoption model, which suggests 5 innovation attributes, which influence the adoption rate of innovations, including compatibility, observability, relative advantage, triability, as well as complexity (Santacreu, 2015). Amongst the 5 attributes, relative advantage is the extent to which, as compared with current products, the innovation is regarded as consumer’s better substitute (Liu et al., 2017). According to Benhabib et al. (2017), compatibility is the extent to which potential users consider an innovation to be consistent with other existing needs, values, as well as past experiences. Complexity is the extent to which it is difficult using an innovation whilst triability is the degree to which prior to adopting, an innovation can be experienced (Wu & Chiu, 2015). Finally, observability is the degree to which an innovation’s outcomes are observable to other individuals (Liu et al., 2017). Notably, of the five attributes, complexity is the one having a negative connection with innovation adoption, whereas others are positively related. Overall, the IDT can be applied to consumer’s behavior towards Airbnb, owing to the fact that it is an innovation (Liu et al., 2017). Essentially, the IDT explains how over time, Airbnb has been able to gain momentum and it has also been able to diffuse through the online platform. As a result, Lu & Tabari (2019) point out that the diffusion has made consumers to adopt to it, which after considering its benefits, have overlooked hotels as an option. The figure below illustrates the Innovation Diffusion Theory.

2.5 Technology Acceptance Model

Technology Acceptance Model (TAM) is used in investigating people’s intentions towards using a new technology. The aim of this model is to determine the factors influencing people’s acceptance of valid measurements, as it explains the usefulness, as well as perceived ease of using a technology (Marangunić & Granić, 2015). Perceived usefulness refers to the extent to which a person believes that his or her job would gain strength in an instance where he or she uses a specific system, and as such, perceived ease of use refers to the extent to which individuals believe that they would require little to no effort in using an innovation. Notably, according to Wu & Chen (2017), both of these determinants are affected by significant external variables. On the other hand, Ooi et al. (2016) states that perceived enjoyment also affects individual intentions towards using a new technology. In this regard, perceived enjoyment implies that people consider using Airbnb to be enjoyable regardless of the aftermath consequences (Muk & Chung, 2015). Overall, millennials have a salient belief that adopting Airbnb would improve their performance whereas perceived ease of use is the millennials’ belief that using Airbnb is effortless.

2.6 Motivation: UK millennials’ preferences of Airbnbs to Hotels

2.6.1 Price value

According to the research conducted by Hockenson (2013), Airbnb’s rooms, as well as apartments are usually significantly cheaper as compared to hotel charges. In this regard, on average, Airbnb apartment rentals are notably 21.1% less expensive as compared to hotel rooms in the UK. Additionally, a private room that is in an apartment is also averagely 49.5% cheaper in the UK (Guttentag et al., 2018). Noteworthy, Guttentag et al. (2015) states that Airbnb can easily undercut its hotel rooms in a larger part, owing to lack of overhead. Pricing is acknowledged to be amongst the most critical factors that determine the long-term success of accommodation in the hotel and tourism industry (So et al., 2018). Essentially, according to Lampinen & Cheshire (2016), price is amongst the influential factors that enable millennials to make travel-related decisions that include selection of their destinations. However, in a hedonic consumption such as tourism, higher prices often do not act against demand. Millennials that are motivated by cultural interests are often less reluctant towards paying more than expected when they need to enjoy cultural traits of various destinations (Bancoro & Batra 2018). The advantages associated with peer-to-peer accommodation include social experiences, as well as low costs. Notably, Guttentag (2016) notes that these appeals purpose to support specific destination that millennials may wish to include in their traveler’s early, as well as late considerations. Additionally, price value or economic benefits are as well as major factors that drive consumer decisions towards using Airbnb (Guttentag, 2016). Generally, the cost-saving features of Airbnb suggest that economic appeal is the most significant factor that encourages millennials to opt for Airbnb instead of hotels, especially when they need to use peer-to-peer accommodation (Guttentag, 2019).

2.6.2 Authenticity

Airbnb has a unique value proposition than hotels, owing to the fact that it has a central character of providing unique, as well as authentic local experience to its consumers (Wang & Jeong, 2018). Notably, Airbnb provides a peer-to-peer accommodation platform, bridges significant channel for consumers, to acquire a unique, as well as authentic experience by residing in a local residential house or a room and interacting with local people. Volgger et al. (2019) note that this is unlike hotels, owing to the fact that they do not provide such authentic services. Notably, the unique, and also the local experience that Airbnb provides is amongst the strongest motivation to millennials to use Airbnb and overlook hotels. It is evident that most millennials prefer standardization and as such, they need more customized services. In line with this, Lutz & Newlands (2018) stress that most of them prefer unique experiences, owing to differences in preferences, as well as their experiences. According to Lin et al. (2017), over the years, the unique, as well as authentic local experience has been meaningful in explaining and comprehending the rapid developments that Airbnb has experienced and the high demand it has received from guests (millennials) as compared to hotels in the UK. The shared economy (Airbnb) has become a game changer, in providing an online platform, as it has the possibility of connecting millennials with more local and also authentic experiences, especially in a host destination (Bancoro & Batra, 2018). Overall, it is worth noting that millennials prefer Airbnb to hotels as they have the privilege of choosing any local individual house or a room whilst they get different, as well as unique experience. These significant factors are not provided by hotels in the UK (Lampinen & Cheshire, 2016).

2.6.3 Enjoyment

Enjoyment poses as a hedonic motivation that determines consumers’ acceptance of an innovation. In accordance to Self-Determination Theory (SDT), motivation can be categorized as intrinsic or extrinsic (Lampinen & Cheshire, 2016). In this regard, intrinsic motivation generates from intrinsic enjoyment/value. In other words, enjoyment is generated from the activity itself. Considering software and technology literature, open-sourced projects contribute an enjoyment feeling and millennials can acquire fun from the use of a new technology. According to Belk (2014), Airbnb provides a peer-to-peer online platform, in which case when consumers browse, they put their knowledge, technology, as well as spent time, and other resources. As such, they are also able to leave their comments on the online platform, and this can be shared with other individuals (Fromm, 2019). Notably, the value-in-use would be derived when millennials use the platform whilst enjoyment would be derived from the entire process. Guibourg & Peachey (2019) states that when millennials live in local houses, they use the resources available in deriving value for themselves, which ultimately leads to enjoyment of the pleasant by using the apartments or rooms. Notably, millennials prefer booking on Airbnb with the intention of enjoying themselves with the resources available in the rooms or apartments, yet are missing in hotels (Hockenson, 2013). In line with this, they desire a specific experience that is connected with interaction with local experience and this attitude significantly influences the behavior of preferring Airbnb to hotels in the UK (Gurran & Phibbs, 2017).

2.6.4 Social interaction

Interaction is just the activities of interacting with local people, as well as the host and thus getting insider tips on the local attractions (Guttentag, 2015). S-D logic scholars indicate that interaction concept poses as a central and also a productive option to the logic of service and also a generator of value-in-use, and service experience. The opportunity derived from personal interaction plays a vital role when consumers decide to stay at an Airbnb residence. Notably, Guttentag (2019) points out that millennials who choose to reside at Airbnb apartments or rooms are capable of knowing new people and this acts as a motivation to prefer Airbnb to hotels in the UK. The actions of providers, customers, as well as other participants’ actions can be grouped according to spheres and in this regard, their interactions result into varied forms of value creation and co-creation (Lu & Tabari, 2019). Noteworthy, the interaction between guests and hosts occurs when they use Airbnb. However, this opportunity is limited when millennials book stay in hotels as they may experience cases of social discrimination (Liang, 2015). The interaction poses as a social appeal of significant local interactions where the guests obtain insiders’ local tips. When millennials live in local houses provided by Airbnb, they are privileged to interact with other individuals apart from the host, including neighbors, and other consumers through online platform by their consumption context. Mody et al. (2019) make it clear that of importance to note is the fact that the interaction is often peer-to-peer for the entire process within which there is the creation of value-in-use.

2.6.5 Home benefits

Home benefits are the household amenities that pose a strong motivation to consumers who prefer Airbnb (Guttentag, 2019). Notably, millennials choose Airbnb over hotels as Airbnb provides them with the opportunity of choosing an accommodation that entails a “homely feeling” and also a large amount of space whenever they desire to choose their destinations. Notably, home benefits are functional attributes of a suitable home. Guttentag (2015) conducted an interview, where consumers indicated that having a personal kitchen was regarded as one of the foremost motivations that enabled them to prefer Airbnb to hotels. S-D logic aids in explaining the value associated with co-creation of Airbnb and it is evident that Airbnb home has resources that are key in terms of enhancing co-creation value. Essentially, Oskam & Boswijk (2016) discovered that the context of Airbnb apartments and rooms provide functional facilities that are regarded as vital resources that benefit consumers. In this regard, home benefit is regarded as a significant motivator for millennials to choose Airbnb over hotels (Nguyen, 2014).

2.6.6 Trust

Trustworthiness deals with the manner by which a person assesses the other individual producing information (Oskam & Boswijk, 2016). Trust enables the movement from intention to action. Based on the peer-to-peer interactions provided by Airbnb, trust, which is a psychosocial construction is established. According to Liang (2015), psychosocial construction is a subjective expression of the expectations of one actor on the behavior of another. As an online platform, trust is seen as an expectation that arises in a community that prioritizes regular, honest, as well as co-operative behavior that are based on a common norm (Sthapit & Björk, 2019). Millennials prefer Airbnb to hotels, owing to the fact that hosts are more trustworthy as compared to hotel attendant.

3.0 Methodology

3.1 Introduction

This chapter provides the research design, as well as the methods that were employed for this study. Notably, this chapter employed quantitative research to explore the factors motivating millennials to choose Airbnb over hotels in the UK. The provisions in this chapter are helpful in meeting the objectives of the study.

3.2 Research design

Primarily, this study purposes to find out the motivations of millennials in the UK towards Airbnb and thus, provide the reasons why millennials in the UK prefer Airbnb to hotels. This study used quantitative research by use of an online questionnaire survey. Creswell & Creswell (2017) state that quantitative research focuses on quantification in the collection of data, as well as analysis process. The primary purposes of using quantitative research in this study were firstly; because it is much reliable and objective (Bryman, 2017). Secondly, and more importantly it is helpful in quantifying a problem by generating significant numerical data or rather, data that can easily be transformed into usable statistics, thus enabling the researcher to quantify the participants’ opinions, behaviors, attitudes, as well as other defined variables (Patten& Newhart, 2017).

3.3 Sample profile of the participants

This study strictly investigated millennials, owing to the fact that this generation expects more for creativity, as well as innovation. Moreover, they were selected for this study, as they are the target market for alternative lodging. The sample size for this study was 50 and the respondents who traveled less than twice in a year were exempted, owing to the fact that this study only aimed at identifying the influential factors on traveler’s selection of either Airbnb or hotels. The demographic, as well as the income situation of the participants were as follows: Considering their ages, it is evident that this study used participants between the ages of 20 to 50 years old, whereby, most of the participants were concentrated within the age bracket of 26-30 years. Whilst considering the gender of the participants, it is evident that 60% of the participants were females whereas 40% of them were males. In terms of the participants’ annual income, most of the participants earned £20,000-£25,000 annually. Moreover, 30 of the participants were married, whereas 20 of them were single.

3.4 Measurements

In order to examine this study’s research model, 10 measurement items were utilized in measuring 6 constructs in the formulated questionnaire. Notably, these items were derived from literature review. Thereafter, they were adjusted to fit this study based on the perception of millennials in the UK towards Airbnb and hotels. In order to comprehend how the participants agreed or disagreed on the items, this study used the 5-point Likert scale in ranging the degree in the questionnaires.

3.5 Control variables

Following an initial study conducted by So et al. (2018), this study chose gender, age, annual income, as well as marital status as control variables.

3.6 Data collection process

Considering the measurements, as well as the constructs operationalization, an online questionnaire survey was prepared. Prior to delivering these questionnaires to travelers in the UK, a pilot study was conducted among 5 travelers, in order to ascertain that they were clear and also understandable. By use of convenience sampling the online survey was distributed through Mturk (Amazon’s Mechanical Turk) (Buhrmester et al., 2018). Buhrmester et al. (2018) further states that Mturk offers individuals access an on-demand scalable workforce. People can select one online survey from the thousands that are posted and thus, complete them for a given time period as assigned by the developers of the survey (Nardi, 2018). Data was collected for a period of weeks, in which case, the participants were given ample time to answer the questions appropriately. The data were then collected back for analysis.

3.7 Statistical tests

Version 22 of the IBM SPSS was used in analyzing data collected from the questionnaires. The reliability of the measurement items were tested through reliability analysis (Cronk, 2016).

3.8 Reliability and validity

Reliability tests the internal consistency of various measurement items. In measuring the reliability of the items, SPSS was used in scaling all the presented variables (Hartas, 2015). On the other hand, validity refers to whether or not, the indicator gauging the concept purposes to measure the concept (Bell et al., 2018). By using questionnaires derived from other previous researches, this study was able to generalize the concept and this ensured validity of the measurement (Heale & Twycross, 2015).

3.9 Ethical considerations

When planning the online questionnaires, the researcher put into consideration various ethical concerns. In this regard, the participants were informed, prior to conducting the research, in order to avoid any unnecessary misunderstandings (Patten & Newhart, 2017). Moreover, the researcher ensured anonymity of the participants, whereby, they were not required to provide any personal information about them (Watson, 2015). Confidentiality was as well assured, and in this case, once the filled questionnaires were submitted back to the researcher, no other third party was allowed to access them. Finally, the participants were allowed to withdraw from participating, as their consent to participate was given topmost priority (Riff et al., 2019).

4.0 Results and discussion

4.1 Introduction

This chapter provides the results of the quantitative research derived from the online questionnaires collected from the participants. This will be followed by a discussion of the findings, which will be backed up with evidence from literature.

4.2 Results of quantitative research

4.2.1 Control variables

As per the table, 42% participants were aged between 26-30 years, 38% between 31-50 and remaining 20% between 20-25 years.

Majority of the participants (60%) were female and 40% were male.

Among all the participants, 32% earn between pounds 20-25k per annum, 28% earn between pounds 26-30k, 20% earn between pounds 31-35k and remaining 20% earn between pounds 36-40k.

60% of the participants were married and remaining 40% were unmarried.

4.2.2. T-Test

Hypothesis one: Price value positively influences millennials’ attitude towards choosing Airbnb over staying in hotels

Airbnb accommodations are reasonably priced as compared to hotels

The mean for the response comes out to be 4.6 with t(49) = 15.2; p < 0.05. Showing that Airbnb accommodations are reasonably priced as compared to hotels

Airbnb offers better accommodations than hotels of the same price

The mean for the response comes out to be 3.8 with t(49) = 4.55; p < 0.05. Showing that Airbnb offers better accommodations than hotels of the same price

Hypothesis two: Authenticity positively influences millennials’ attitude towards choosing Airbnb over staying in hotels

Airbnb tends to provide an authentic local experience than hotels

The mean for the response comes out to be 4.88 with t(49) = 34.48; p < 0.05. Showing that Airbnb tends to provide an authentic local experience than hotels

Airbnb tends to offer a unique experience.

a. t cannot be computed because the standard deviation is 0.

All the respondents strongly agreed.

Hypothesis three: Enjoyment positively influences millennials’ attitude towards choosing Airbnb over staying in hotels

Staying at Airbnb is fun than in hotel

The mean for the response comes out to be 4.14 with t(49) = 6.08; p < 0.05. Showing that Staying at Airbnb is fun than in hotel

Staying at Airbnb offers an entertaining experience than staying in a hotel

The mean for the response comes out to be 3.14 with t(49) = 0.739; p > 0.05. Showing that Staying at Airbnb do not offers an entertaining experience than staying in an hotel

Hypothesis four: Social interaction positively influences millennials’ attitude towards choosing Airbnb over staying in hotels

Airbnb offers guests opportunities to interact more directly with local people, hosts, and other guests

The mean for the response comes out to be 4.9 with t(49) = 44.33; p < 0.05. Showing that Airbnb offers guests opportunities to interact more directly with local people, hosts, and other guests

Hypothesis five: Home benefit positively influences millennials’ attitude towards choosing Airbnb over staying in hotels

Airbnb provides a “homely” feel during the stay

The mean for the response comes out to be 4.48 with t(49) = 8.98; p < 0.05. Showing that Airbnb provides a “homely” feel during the stay

Airbnb safeguards the best interests of customers as compared to hotels

The mean for the response comes out to be 3 with t(49) = 0.00; p > 0.05. Showing that Airbnb do not safeguards the best interests of customers as compared to hotels

Hypothesis six: Trust positively influences millennials’ attitude towards choosing Airbnb over staying in hotels

Airbnb enforces trustworthiness as compared to hotels

The mean for the response comes out to be 3.76 with t(49) = 4.97; p < 0.05. Showing that Airbnb enforces trustworthiness as compared to hotels

4.3 Discussion of the findings

4.3.1 Price value

Hypothesis one: Price value positively influences millennials’ attitude towards choosing Airbnb over staying in hotels. This hypothesis is supported by the quantitative research conducted in this study. Oskam & Boswijk (2016) discovered that price poses as one of the most vital factors that need to be considered in the accommodation industry, and it is also an influential factor that aids millennials in making travel-related decisions. Overall, it is evident that this result indicates that although Airbnb takes a different model from hotels, the price value significantly affects millennials (Nguyen, 2014).

Authenticity

Hypothesis two: Authenticity positively influences millennials’ attitude towards choosing Airbnb over staying in hotels. This hypothesis is supported by quantitative research when considered together with other motivation factors in the proposed model in this study. A study conducted by So et al. (2018) points out that authenticity is a significant factor that millennials consider in the UK when having an option of either Airbnb or hotels. As compared to hotels, authenticity implies that millennials are able to access various local experiences by opting for Airbnb, especially when they have peer-to-peer connection with either the local life of local hosts (Oskam & Boswijk, 2016). In this regard, authenticity poses as a motivator for millennials to choose Airbnb over hotels.

Enjoyment

Hypothesis three: Enjoyment positively influences millennials’ attitude towards choosing Airbnb over staying in hotels, This hypothesis has been supported by quantitative research provided by this study. According to the research conducted by Hockenson (2013), the enjoyment derived from Airbnb originates from intrinsic value or enjoyment from the process of utilizing the platform with technology, as well as from interaction with local hosts (Guttentag, 2019; So et al., 2018). Notably, enjoyment is demonstrated as a value-in-use in the process when millennials use Airbnb online platform, thus deriving enjoyment from the sharing of apartments with hosts, and other consumers (Guttentag, 2019).

Social interaction

Hypothesis four: Social interaction positively influences millennials’ attitude towards choosing Airbnb over staying in hotels. As supported by the quantitative research, this result is also supported by the study of So et al. (2018), which stresses that social interaction is a major factor for millennials as they prefer choosing collaborative consumption whilst having the dire to connect, and also communicate with their local hosts (Guttentag, 2016). This then illustrates the fact that most millennials prefer the trend of choosing to share with their hosts, as well as other guests, in order to have a social interaction, which is limited in hotels (Guttentag, 2015).

Home benefit

Hypothesis five: Home benefit positively influences millennials’ attitude towards choosing Airbnb over staying in hotels. This hypothesis is supported by the quantitative research. Notably, Oskam & Boswijk (2016) stated that home benefits whilst relating it to Airbnb refers to household amenities, and it is regarded as a strong motivation, especially when millennials choose Airbnb for accommodation over hotels. Essentially, Oskam & Boswijk (2016) also discovered that the context of Airbnb apartments and rooms provide functional facilities that are regarded as vital resources that benefit millennials.

Trust

Hypothesis six: Trust positively influences millennials’ attitude towards choosing Airbnb over staying in hotels. This hypothesis was supported by the quantitative research. Notably, trust poses as the core and the foundation of sharing. In this regard, establishing trust among strangers is regarded as a key towards the development of a sharing economy (Oskam & Boswijk, 2016). Owing to the fact that Airbnb provides a peer-to-peer platform, it connects guests, as well as hosts. However, the trust system needs to be established over a long time. Essentially, According to Liang (2015), distrusts significantly constraints millennials in the UK from choosing hotels. Distrust, according to this dissertation, is the lack of inter-personal trust existing between hosts and guests, lack towards the technology, as well as lack of trust towards the company. Presently in the UK, online business is common for millennials as they find it easy for them to adapt to the model (Sthapit & Björk, 2019).

Conclusion

This thesis has proposed a total of 6 hypothesis on the factors that affect millennials’ attitude towards Airbnb, which are supported by the results from the quantitative research. The six factors that were tested include price value, enjoyment, trust, home benefits authenticity, as well as social interaction. E-commerce is fast developing in the UK and as such, millennials are overlooking the importance of hotels. Generally, the cost-saving features of Airbnb suggest that economic appeal is the most significant factor that encourages millennials to opt for Airbnb instead of hotels, especially when they need to use peer-to-peer accommodation (Guttentag, 2019). Considering authenticity, millennials prefer Airbnb to hotels as they have the privilege of choosing any local individual house or a room whilst they get different, as well as unique experience. Moreover, millennials prefer booking on Airbnb with the intention of enjoying themselves with the resources available in the rooms or apartments, yet are missing in hotels (Hockenson, 2013). Of importance to note, is the fact that millennials live in local houses provided by Airbnb, they are privileged to interact with other individuals apart from the host, including neighbors, and other consumers through online platform by their consumption context (Mody et al., 2019). Oskam & Boswijk (2016) discovered that the context of Airbnb apartments and rooms provide functional facilities that are regarded as vital resources that benefit consumers. In this regard, home benefit is regarded as a significant motivator for millennials to choose Airbnb over hotels. Finally, millennials prefer Airbnb to hotels, owing to the fact that hosts are more trustworthy as compared to hotel attendant (Oskam & Boswijk, 2016).

Implication

Since Airbnb entered the UK, it is believed to have the biggest challenge, in terms of localization. Airbnb had the belief that it would strive, in order to enhance overseas tourism experience in a short term (Oskam & Boswijk, 2016). However, Guttentag et al. (2015) state that its exposure to the UK market implies that it has to be involved into the UK as soon as possible. This study is about the contributions of Airbnb, as well as the short-term rental providers, which then provides significant information regarding the factors that could purposely influence millennials’ attitude in the UK. Overall, the information that this thesis provides is a significant contribution. However, it is evident that this study has provided less academic research, as it focuses on the UK millennial consumers on their preferences towards accommodation options, which is a broad area of concern.

Recommendation

This thesis brings forth the following recommendations:

Considering the fact that enjoyment and trust play the most vital roles in motivating the UK millennials to use Airbnb, it is recommendable that Airbnb should purpose to improve friendliness in the Airbnb online platform, and also improve the entire process that involves the provision of various services. This is primarily to improve value-in-use for the enjoyment of millennials to increase accordingly. Additionally, there should be improvement of trust between Airbnb and its guests in all aspects (So et al., 2018).

Secondly, insecurity can be the most significant factor that can constrain the UK millennials from choosing Airbnb. Therefore, it is recommended that Airbnb should purpose to improve the level of insecurity when consumers live in local individual houses. In this regard, Airbnb can opt to improve the qualification of its hosts, and also strengthen its cooperation with the local government with the aim of improving security, and providing more guarantee to its consumers (Bancoro & Batra 2018).

Limitation and future research

Firstly, the UK has a large population and they reside in different areas, thus, implying that there exist huge differences when considering various factors such as living habits. In other words, millennials from different areas may have a different attitude towards Airbnb or they may be influenced by different factors (Bancoro & Batra 2018). In this regard, if the UK consumers are divided into different areas, different results may be obtained. In the future studies, there may be need to investigate the consumers, based on area distinction, in order to understand the consumers better, under a narrow scope. Secondly, this dissertation does not discriminate whether the UK millennials choose overseas accommodation or they just choose accommodation in the UK in different areas, owing to the fact that language problem may limit the consumers that are not able to speak other language to prefer Airbnb, for instance, in a Chinese-speaking country (Guttentag, 2019). For future studies, it will be significant for language factor to be included as a control factor, owing to the opinion that maybe, a different result can be obtained.

References

Abraham, C., & Sheeran, P. (2017). Implications of goal theories for the theories of reasoned action and planned behavior. In Planned Behavior (pp. 101-122). Routledge.

Bancoro, A. I. M., & Batra, A. (2018, October). Tourists’ Motivation in Using Sharing Accommodation in Bangkok. In Global Conference on Business, Hospitality, and Tourism Research (GLOSEARCH 2018).

Belk, R. (2014). You are what you can access: Sharing and collaborative consumption online. Journal of business research, 67(8), 1595-1600.

Bell, E., Bryman, A., & Harley, B. (2018). Business research methods. Oxford university press.

Benhabib, J., Perla, J., & Tonetti, C. (2017). Reconciling models of diffusion and innovation: a theory of the productivity distribution and technology frontier (No. w23095). National Bureau of Economic Research.

Buhrmester, M. D., Talaifar, S., & Gosling, S. D. (2018). An evaluation of Amazon’s Mechanical Turk, its rapid rise, and its effective use. Perspectives on Psychological Science, 13(2), 149-154.

Cronk, B. C. (2016). How to use IBM SPSS statistics: A step-by-step guide to analysis and interpretation. Routledge.

Gutiérrez, J., García-Palomares, J. C., Romanillos, G., & Salas-Olmedo, M. H. (2017). The eruption of Airbnb in tourist cities: Comparing spatial patterns of hotels and peer-to-peer accommodation in Barcelona. Tourism Management, 62, 278-291.

Hartas, D. (Ed.). (2015). Educational research and inquiry: Qualitative and quantitative approaches. Bloomsbury Publishing.

Kautonen, T., van Gelderen, M., & Fink, M. (2015). Robustness of the theory of planned behavior in predicting entrepreneurial intentions and actions. Entrepreneurship Theory and Practice, 39(3), 655-674.

Ladhari, R., & Michaud, M. (2015). eWOM effects on hotel booking intentions, attitudes, trust, and website perceptions. International Journal of Hospitality Management, 46, 36-45.

Lin, H. Y., Wang, M. H., & Wu, M. J. (2017). A Study Of Airbnb Use Behavior In The Sharing Economy. International Journal of Organizational Innovation, 10(1).

Lutz, C., & Newlands, G. (2018). Consumer segmentation within the sharing economy: The case of Airbnb. Journal of Business Research, 88, 187-196.

Mody, M., Suess, C., & Lehto, X. (2019). Going back to its roots: can hospitableness provide hotels competitive advantage over the sharing economy?. International Journal of Hospitality Management, 76, 286-298.

Ooi, K. B., & Tan, G. W. H. (2016). Mobile technology acceptance model: An investigation using mobile users to explore smartphone credit card. Expert Systems with Applications, 59, 33-46.

Paul, J., Modi, A., & Patel, J. (2016). Predicting green product consumption using theory of planned behavior and reasoned action. Journal of retailing and consumer services, 29, 123-134.

So, K. K. F., Oh, H., & Min, S. (2018). Motivations and constraints of Airbnb consumers: Findings from a mixed-methods approach. Tourism Management, 67, 224-236.

Soomro, B. A., & Shah, N. (2015). Developing attitudes and intentions among potential entrepreneurs. Journal of Enterprise Information Management, 28(2), 304-322.

Volgger, M., Taplin, R., & Pforr, C. (2019). The evolution of ‘Airbnb-tourism’: Demand-side dynamics around international use of peer-to-peer accommodation in Australia. Annals of Tourism Research, 75, 322-337.

Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221-232.

Wu, L., & Chiu, M. L. (2015). Organizational applications of IT innovation and firm's competitive performance: A resource-based view and the innovation diffusion approach. Journal of Engineering and Technology Management, 35, 25-44.