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The Effect of Electronic Word of Mouth on Intention to Book Accommodation via Online Peer-to-Peer Platform: Investigation of Theory of Planned Behaviour

See-Kwong Goh*
Taylor’s Business School, Taylor’s University, Lakeside Campus, No. 1 Jalan Taylor’s, 47500 Subang Jaya, Selangor, Malaysia
Corresponding Author: See-Kwong Goh, Taylor’s Business School, Taylor’s University, Lakeside Campus, Taylor’s, 47500 Subang Jaya, Selangor, Malaysia, Tel: +60122085756; E-mail: seekwong.goh@taylors.edu.my
Received October 09, 2015; Accepted November 29, 2015; Published December 02, 2015
Citation: Goh SK (2015) The Effect of Electronic Word of Mouth on Intention to Book Accommodation via Online Peer-to-Peer Platform: Investigation of Theory of Planned Behaviour. J Internet Bank Commer S2:005.
Copyright: © 2015 Goh SK. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Abstract

The main purpose for conducting the research is to investigate whether positive eWOM received by consumers would influence their intention to book accommodation via a peer-to-peer website or mobile phone apps (such as Airbnb). The research was conducted by utilizing the Theory of Planned Behaviour which integrates the eWOM, attitude, subjective norms, perceived behavioural control and behavioural intention. A total of 226 responses had been recorded. The main findings from this research are related to the key role played by positive eWOM received towards an individual’s attitude, subjective norm and perceived behavioural control which influences their intention to book their accommodation through an online peer-to-peer platform.

Keywords

eWOM; Theory of planned behaviour; Malaysia; Peer-topeer; Accommodation

Introduction

Technological advances around the world have provided new form of advertising mechanism. The introduction of ‘web 2.0’ technology whereby marketing is done mainly through the use of the internet or social medias such as Facebook and Twitter. Based on previous researches, it shows that word of mouth through social media plays a vital role in influencing consumers’ decision making. Word of mouth is defined as the face-to-face communication between people that allows them to communication in an unbiased manner regarding products or services in a platform believed to be non-related with an organization. According to Brown [1], their findings had shown that WOM holds a powerful force in shaping the attitudes and behaviour of consumers. To further support this finding, studies conducted by Mazzarol et al. [2] and Sweeney et al. [3] had also proven that WOM communications greatly influences consumers’ attitudinal and behavioural disposition especially within the service industries. Besides, WOM is also said to carry greater influence on product adoption as compared to other mass media advertising [4-6]. In addition, Day [7] has suggested that WOM communication is nine times more effective in changing an individual’s unfavourable disposition to a favourable disposition as compared to print and media communication.
As the internet gains popularity, it had established a more universal and less personal kind of WOM which is Electronic Word of Mouth (eWOM) [1,8,9]. According to Hennig-Thurau et al. [10], eWOM is defined as comments either positive or negative which are made by customers regarding a company or a product to a significant amount of people through the Internet. eWOM is also considered to be an important platform that lets consumers to communicate their thoughts to others [11-13]. In addition, eWOM is also considered to be more effective when compared to traditional word of mouth as it is more convenience and it has the ability to achieve a higher reach [14].
According to Bickart [11] and Sen [15], one of the most significant kinds of digital WOM is the postage of online reviews by consumers. It is also stated that conducting online reviews to obtain information prior to making a purchase is becoming increasingly common among consumers [16,17]. In addition, a study conducted by Xia [9] suggests consumers assess electronic reviews to be more trustworthy and useful which results in a greater purchase intention. Furthermore, another study conducted by MacKinnon [18] depicted that consumers today rely heavily on user generated content and word of mouth through online reviews while making their purchasing decisions. In addition, consumers also trust this content more as compared to those from advertisers [18]. Moreover, previous studies have shown that consumers rely on online reviews when planning a trip, making a hotel or restaurant reservation [19]. This is due to the nature of the service industry which is intangible and hard measure, consumers often rely on past comments and eWOM to support their decision [20]. As such, in order to evaluate how eWOM affects one’s decision in selecting accommodation (through a peer-to-peer platform), we need to identify to what extend does eWOM influence a person’s behaviour in choosing accommodation via a peer-to-peer platform or application (such as Airbnb).
The concept of peer-to-peer mobile application or online website on accommodation has gained its popularity in the early 2011. Consumers or tourists have the additional option to select an accommodation which is owned by another consumer. These peer-to-peer platforms enable owners of a house, apartment or room to rent their property out to tourist or guest for a short or long stay through a website or mobile application. The website or mobile application would also provide the option for guest to rate the host, owner or property and also provides the opportunity for one to leave a comment or review after the stay. Since these are not large hotel chains or commercial accommodation providers, rating and reviews serves as the key source of information influencing consumers’ decision in selecting a place. Therefore, it is crucial to evaluate how these eWOM affect behavioural intention of a typical consumer in making his or her decision in selecting accommodation via peer-to-peer platform.
In order to determine the interrelationship between eWOM and behaviour within the peer-to-peer accommodation context, the research would first investigate the utilization of eWOM among consumers. Next, the impact of eWOM on consumers’ intention towards booking accommodation via peer-to-peer platform would be measured. On the other hand, consumers’ behavioural intention would be tested by using Ajzen’s [21] theory of planned behavioural model (TPB) as it is among the most comprehensive tools to test consumers’ behavioural intention. Furthermore, this model was previously used in researches within the restaurant and tourism industry [8,22-24].

Electronic Word of Mouth (E-WOM)

According to Hennig-Thurau et al. [10] whenever any good or bad comments are made to a significant amount of individuals or organizations on the internet, it is known as Electronic Word of Mouth or (eWOM). Whereas, Godes [13] and Park et al. [25] added that differences exists between eWOM and traditional advertisements because eWOM is an independent statement generated by customers regarding their experience which influences the buying decision of other customers.
eWOM also provides online information seekers with wider and more diverse sources of positive and negative information as compared to tradition WOM [14]. Furthermore, Bickart [11] suggest that consumers have higher level of interest regarding a product topic if they gathered the information themselves through online discussion as compared to market generated sources. On the influence front, Godes [13] states that eWOM have greater influence towards a consumer attitude and view regarding a brand as compared to other influential sources.
Besides, several studies have shown that consumer’s places more trusts towards eWOM. In addition, Huang [26] states that consumers seeking information online believes that online consumer recommendations are more trustworthy as compared to information generated by experts. Furthermore, eWOM was also proven to be an important reference within the travel industry for consumers when they are making travel decisions and also other choices of travel products such as hotels and restaurants [27-29].

Theory of Planned Behaviour

The theory of planned behaviour (TPB) model was developed by Ajzen [21,30] as an addition to the Theory of Reasoned Action (TRA). The TRA model is related to social psychology as it assumes humans to be logical while systematically using information that are accessible to them. Furthermore, the model states that individuals would ponder on the consequences involve prior to making any decisions to take part or not to the part in any behaviour [31]. This extension adds the construct of perceived behavioural control as opposed to only using attitudes and subjective norms to predict behavioural intention [32]. This was needed due to TRA’s inability to deal with individuals who have incomplete volitional control. In general, the TPB model assumes control over actions whereas the TRA model does not. According to Sheppard et al. [33], the TPB model is one of the most influential theories in explaining and predicting behaviours.
The TPB model describes how people are likely to perform a particular behaviour by believing that it leads to a positive outcome, coupled with the approval from important referents and also the necessary abilities, resources, and opportunities to conduct such behaviour [34,35]. According to the TPB model, an individual’s intention to undertake a given behaviour is influenced by his/her attitude towards behaviour, subjective norm and also perception of behavioural control factors [21]. It is said that an individual’s intention is notified by his/her attitude on the behaviour, subjective norm towards participating in the behaviour, and also a person’s assessment revolving around his/her ability to successfully participate towards the focus behaviour.
As stated by Ajzen [21], behavioural Intention plays a pivotal role within the TPB model which signifies the length to which an individual intends to execute or not to execute a certain behaviour. Furthermore Ajzen and Fishbein [31] stressed that actual behaviour can be directly predicted by linking PBC and behavioural intention. According to Ajzen [21]; Ajzen [31] behavioural intention is a key mediator in measuring the affiliation between behaviour and other elements like attitude, subjective norms, and PBC. In fact, since selecting an accommodation is a planned behaviour, TPB is deemed to be used as the underpinning theoretical foundation for this research [36,37].

Attitude towards booking accommodation

Attitude is generally an unrelenting assessment on human, objects and goods [38]. Attitude also enables individuals to repeatedly carry out good or bad reaction on certain situations in a consistence manner via education [39,40]. This involves favourable or unfavourable assessment, emotional feelings, and behavioural propensity [41]. Furthermore, TBP explains attitude towards behaviour as the extent whereby an individual possesses a positive or negative assessment towards the behaviour in question [21]. Hence, it can be said that as attitudes are more favourable toward the behaviour, a person’s intention to execute the behaviour will be stronger [21].
For this study, the aim behaviour would be to book accommodation via a peer-to-peer platform, whereas the attitude would be to make a booking through such platform. Previous research found that attitude directly affects individual’s intention to dine in green restaurants [32]. In addition, a study conducted by Casaló et al. [42] regarding the participation of individuals in an online travel community hosted by a firm coupled with the impact towards using the products of the hosting firm and to recommend the hosting firm had shown a strong link between attitude in participating and intention to participate in such communities.
Several studies have also indicated that WOM plays a dominant part in affecting and developing individuals’ attitudes and behavioural intention [9,15,43,44]. As for information exchange, consumers whom first obtains good/bad information will develop a good/bad attitude which could never be changed even if the individual receives any bad/ good WOM information [43]. Positive WOM also elicit favourable attitude towards a product as compared to negative WOM [45]. Furthermore, attitude towards a given website and the internet plays an important role in explaining consumers’ attitude pertaining to both brand behaviour and their behaviour [46]. Whereas, Dennis et al. [47] shows that e-consumer’s attitude towards a given e-seller will positively influence their buying intention from the given e-seller. In addition, Blogdgett [47] states that behavioural intention is positively influenced by attitude. To strengthen this view, Trafimow [48] conducted a review which shows that 29 out of 30 studies found attitude as the best predictor of intention. Lastly, Beerli [49] had concluded that word of mouth generated from friends and family plays an important role in developing certain image perception of a travel destination towards an individual. Therefore the following hypothesis was proposed:
H_1: eWOM has an impact on attitude towards booking accommodation through a peer-to-peer platform
H_1a: Attitudes toward booking accommodation through a peerto- peer platform has an impact on intention to book an accommodation through a peer-to-peer platform

Subjective norms

The second determination of intention in the TPB model is subjective norm. According to Ajzen [21], subjective norm is the perception of social pressures to undertake or not to undertake a given behaviour. There is also another component towards subject norms which is normative belief. Normative belief is the perceptions of an individual towards the views regarding his/her act towards the behaviour generated by a person believed to be important to that individual. The TPB model suggests that wherever the stronger the drive to adhere to social pressure, the function of social pressure is more important Mathieson [50]. Furthermore, subjective norms used as a basis for intention are also well-recorded Taylor [51]. According to Bearden [52], a person view of a given situation tends to be influenced by the perceived opinions of significant others. They added that social influences are widely recognized to influence consumer behaviour. In addition, Hee [53] stated that individuals uses people that are important to him/her such as parents, relatives, siblings, romantic partner or close friends to act as reference group whenever he/she forms his/her own opinion. Furthermore, it can also be said that the more intense and frequent the communication between an individual and the people that are important to him/her, it increases the likelihood of the given individual to adopt the beliefs and ideas of his/her reference group [54].
Besides, Venkatesh et al. [55] concludes that subjective norm originated through social influences is crucial to ascertain users’ intention towards the acceptance and usage of technology. Several other studies also show that subjective norms influence intention. For instant, subjective norms were found to influence consumer’s intention to use the computing resource center [51], whereas Peace et al. [56] concluded that subjective norm is a major forecaster towards the intention to copy software illegally. In addition, subjective norms also influence consumers’ online purchase intention [57]. Subjective norm is also argued to have a significant affect towards user’s participation within the online community [58]. Besides, peers and outside social influences is also a factor of subjective norms towards consumers regarding technological acceptance [59,60]. According to Bhattacgerjee [61] and Teo [62], peer influences are usually WOM generated by acquaintances, co-workers and relatives. On the other hand, external influences are generated by media intelligences, impersonal information and expert opinions.
In addition, WOM is also said to generate the subjective norm construct wherever consumer considers technology adoption [63]. In terms of studies in the tourism industry, Lam [23] determined that subject norm greatly influences Taiwanese tourist’s intention to visit Hong Kong. Lastly, Bommer et al. [64] and Kreie [65] had evidently proven that subjective norms are influenced by significant others. Therefore the following hypothesis was proposed:
H_2: eWOM has an impact on subjective norms.
H_2a: Subjective norm has an impact on intention to book an accommodation through a peer-to-peer platform.

Perceived Behavioural Control

The third component of TPB is known as perceived behavioural control (PBC). Ajzen [21] defines PBC as an individual’s perception regarding the ease or difficulty in undertaking the behaviour and added that it reflects on past experiences and also expected impediments and consequences. TPB also suggested that PBC directly impacts the intention to perform a behaviour and also the actual performance of that behaviour as compared to the extent of the actual behavioural control. Moreover, Spark [66] view of PBC is similar to Bandura [67] on perceived self-efficacy. In addition, Bandura argued that people’s confidence and ability in performing one behaviour is directly affected by their behaviour.
Furthermore, PBC comprises of 2 different factors namely control beliefs and perceived facilitation. Control beliefs are an individual’s belief concerning the self-availability of skills, resources and opportunities. As for PBC, it is the importance an individual places towards those skills, resources and opportunities in order to achieve a desired outcome.
According to Pavlov [57], PBC has proven to be a significant predictor of intention towards purchasing a product and to obtain information from a web vendor. In addition, a strong link exists between PBC and intention towards participating in an online travel community hosted by a firm [42]. Besides, past researchers conducted by Lam [23] had shown that PBC denotes an important construct in the prediction of consumers’ intention towards visiting a tourist destination. Furthermore, Mathieson [50] states that PBC significantly affects consumers intention to utilize IT. Whereas, Palka et al. [68] had proven that resources based settings could influence mobile recipient’s PBC. Lastly, PBC is proven to be positively related to consumer’s negative word of mouth communication [69]. Therefore, it can be hypothesized that:
H_3: eWOM has an impact on perceived behavioural control.
H_3a: Perceived behavioural control has an impact on intention to book an accommodation through a peer-to-peer platform.
Based on the above hypotheses, this study develops a conceptual framework (Figure 1).

Method

This research adopt a non-random purposive sampling method. This quantitative study gathered empirical data using a self-designed questionnaire among 500 Malaysian consumers within a period of two months. A total of 272 surveys was returned with 226 valid questionnaires (response rate, 45%). Of the 226 respondents, 48% were men and 52% were women. 32% of the respondents were between 18- 29 years of age; 28% were between age group of 30-39 years of age; 22% were between 40-49 years of age; and 18% were greater than 50 years of age. Majority of the respondents (78.7%) had undergraduate education. 49.5% of the respondents were Malay; 32.8% were Chinese; 11.2% were Indians; and 6.5% were others.
To measure the variable constructs within the research framework, a self-administered electronic questionnaire consisting of nominal, ordinal and interval scales where designed. These variable constructs consists of eWOM, attitude, subjective norm, perceived behavioural control and intention. All items were adopted from Jalilvand and Samiei [8]. Data analysis is conducted by using structural equation modelling (SEM AMOS 21), and guided by two-step analysis approach [70]. A 5-point Likert scale was adopted to measure a total of five constructs from ‘strongly disagree (1)’ to ‘strongly agree (5)’. Researchers first evaluate the measurement model before assessing the structural model as “it makes little sense to relate construct within an SEM model if the factors specified as part of the model are not worthy of further attention” [71].

EFA: Uni-diemsionality analysis

Exploratory factor analysis (EFA) is a useful technique for reducing a large set of indicators into a more manageable subset. A typical use of EFA in the development of scales is to factor an overall set of items and then construct scales based on the result of factor loadings [72]. Researchers adopt EFA due to the two following reasons. The first reason is to refine and develop suitable scale (questionnaire) to precisely measure each construct. Thus, items which load lower than 0.6 was eliminated. The next reason of adopting EFA is to assess unidimensionality of each construct, in which a set of indictors share only a single underlying factor. Unidiemsnitonality rigorously address the measurement properties of new and well-established scales [72]. Such properties reveal the accuracy (validity) and consistency (reliability) of construct measurement. Poor measurement properties may lead to erroneous conclusions regarding the existence, magnitude and director of association between constructs. Therefore, items whose cross loading higher than 0.4 were eliminated. The finalized items and related factor loadings are presented in Table 1. There is no violation of unidiemsional measurement of each construct in this study.

CFA: Convergent and discriminant validities

As shown in Table 1, each construct is measured by multiple indicators. Although EFA can confirm that each indicator measures only a single construct, only CFA is able to provide more accurate assessment of unidimentionality and directly provide quantifiable evidence regarding the external and internal consistency among a set of construct indicators [72,73]. The aforementioned internal consistency is reflected by convergent validity (composite reliability and average variance extract); and the external consistency is reflected by discriminant validity. Since the social and behavioural sciences have learnt much more from confirmatory factor analysis (CFA) than from structural equation modeling (SEM) [74], this research adopted Anderson and Gerbing’s [70] two-step approach to conduct confirmatory factor analysis (CFA) and further confirm unidimensionality through convergent and discriminant validity tests.
According to Anderson and Gerbing [70], two-step approach, a confirmatory factor analysis (CFA) is conducted first in order to establish confidence in the measurement model, which specifies the posited relation of the observed variables to the underlying constructs. One of the primary objectives of CFA/SEM is to assess the extent to which a set of measured items actually reflects the theoretical latent construct [75]. Thus, this research assesses the adequacy of each multiitem scale in capturing constructs validity in measurement models (Table 2).
The standardized loading estimates of all items are significant (p < 0.001) and higher than 0.6 (Anderson and Gerbin, 1988; Hair, 2010). The average variance extracted (AVE) estimates are between 0.603 and 0.694 (above 0.5) [76,77] and construct reliability (CR) of each construct is between 0.819 and 0.900 (above 0.7) [78], which reveals that the convergent validity was achieved.
Discriminant validity assesses the extent to which a construct is truly distinct from other constructs [75]. Although the correlation (Pearson’s R) among constructs can be used to detect the issue of muticollinearity, there is no firm rule that a correlation with other measurements below absolute 0.85 is a cut point. With Anderson and Gerbin’s first step approach (1988), the correlations among six latent variables (Electronic word of mouth: eWOM; Attitude: ATT; Subjective norm: SN; Perceived behavioural control: PBC and Intention: INT) are between 0.346 and 0.659. The AVE square root of each variable is larger than any correlation between that particular variable and any other variables, which reveals that the discriminant validity was achieved and Type II error rate was quite low. There is no issue of multicollinearity among constructs in this study. In addition to EFA (Table 1), unidimensionality was further confirmed through CFA (Table 3).

Analysis result

Following the proposed measurement model, an empirical structural equation model is established in order to test the hypothesized construct model. The goodness-of-fit indices of this model are within an acceptable range (chi-square=185.980, df=135, p 0.001, chi-square/ df=1.3, GFI=0.903, RMSEA=0.046, TLI=0.972, CFI=0.978). As a result, there is no negative error variance of variables or ‘Heywood case’ [79,80]. The standard errors of variance are relatively small between 0.050 and 0.1574.
Research results indicate that all hypotheses tests are statistically significant (Table 4). Electronic word of mouth had a significant effect on attitude (H1, β=0.484, p<0.001), subjective norm (H2, β=0.563, p<0.001) and perceived behavioural control (H1, β=0.396, p<0.001). Meanwhile all paths toward intention to book accommodation via peerto- peer platform are also statistically significant. Perceived behavioural control has the largest effect to behavioural intention (H3a, β=0.497, p<0.001), followed by attitude (H1a, β=0.242, p<0.05) and subjective norm (H2a, β=0.18, p<0.05).

Discussion

This study aims to explain eWOM influences towards consumers’ intention to book accommodation through an online peer-to-peer platform. Although there are many research that are related to eWOM in the tourism industry but there is very little research that emphasise on online peer-to-peer platform. Based on the findings of this research, eWOM significantly, positively, and directly impacts consumers’ attitude towards, subjective norms, and perceived behavioural control [19,61,62]. The findings of this study also validated that attitude, subjective norms and perceived behavioural control as behavioural intention determinants in TPB as all three constructs had found to significantly determine consumers intention to use online peer-topeer applications or website to book their accommodation [34,35]. As accommodations rental are categorized as a service industry, it is believed that a strong indicator towards the selection of accommodation is due to consumers’ attitude towards the accommodation rating and review. If a particular listing has a strong positive eWOM, the higher the attitude towards renting the said accommodation. In addition, the research findings also support Hartwick and Barki [81] claim that subjective norms significantly influences behavioural intention even though consumers are unable to develop attitudes towards information system use due to limited direct experiences. Besides, this research had also evidently confirmed that perceived behavioural control positively and significantly impacts consumers’ intention to use such platform to book accommodation.
The internet had immensely benefited today’s consumers by empowering them the ability to obtain and disseminate product related information. Furthermore, Ward [82] stated that peer generated product information could be easily gathered by consumers today. In addition, individuals could also influence consumers by sharing their own personal experience. Based on result of this study, we recommend the following practical implication for home owners or accommodation host. First, home owners or accommodation host in the peer-to-peer platform could reduce their advertising expenses by encouraging patrons to participate in discussion with online communities. Moreover, the accommodation owner or host could also provide discount or free gifts to encourage patrons to posit their reviews after their visit. If there is a negative review, it has to be addressed in a positive manner in order to avoid loss of potential customers. Second, accommodation owners or hosts should also take proactive measures to ensure that customers constantly are provided with positive experience and subsequently, these positive experience should be translated into reviews and rating online. This helps to generate positive eWOM. Third, managers of these online platforms (such as Airbnb) should also monitor the online reviews provided by guest and visitors. Owners or host that consistently received negative reviews should be removed from the listing while those who always obtained positive reviews should be given incentive. This will ensure that the reputation of the online peer-to-peer platform is maintained as well as it will encourage customers to return for future visits.
The limitation of this paper would be the scope of this research was in Malaysia and the respondents were majority Malaysian. Thus, caution might be advised when generalizing the research finding to different countries or regions. Although research finding pass the test of cross-validation, there is still lack of evidence that similar research results can be discerned in other contexts or different industries. Therefore, further research aims to generalize the conceptual model and compare the results in relatively broader scopes.

Tables at a glance

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Table 1 Table 2 Table 3 Table 4

Figures at a glance

Figure 1
Figure 1

References

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