The Electronic Word-of-Mouth (eWOM) Focusing Studies on Tourism Research
Online Reputation Management in Destination and Hospitality
ISBN: 978-1-80382-376-8, eISBN: 978-1-80382-375-1
Publication date: 9 February 2023
Abstract
Interest in the Electronic Word-of-Mouth (eWOM) in connection with tourism is constantly growing not only among consumers but also among theoreticians. Therefore, the objective of this chapter is to provide an overview of studies that focus on eWOM in the tourism sector using the snowball method. The article is based on a review of the literature of 60 studies that focus not only on consumer behavior in tourism and the impact of eWOM on tourism supply but also on the impact of hotel managers' responses to other consumer behavior and tourism companies. The results of the studies show that eWOM has a significant impact not only on consumer behavior but also on tourism supply. Manager responses can also strongly affect other consumer behavior in decision-making. When eWOM is distributed, consumers are influenced by their emotions, motives, and also by the websites to which they have decided to contribute. The chapter proposes further research areas for different authors.
Keywords
Citation
Medeková, K., Pompurová, K. and Šimočková, I. (2023), "The Electronic Word-of-Mouth (eWOM) Focusing Studies on Tourism Research", Rialti, R., Kvítková, Z. and Makovník, T. (Ed.) Online Reputation Management in Destination and Hospitality, Emerald Publishing Limited, Leeds, pp. 29-49. https://doi.org/10.1108/978-1-80382-375-120231002
Publisher
:Emerald Publishing Limited
Copyright © 2023 Kristína Medeková, Kristína Pompurová and Ivana Šimočková. Published under exclusive licence by Emerald Publishing Limited
2.1 Introduction
Liu, Osburg, Yoganathan, and Cartwright (2021) confirm the increasing interest in electronic word-of-mouth (eWOM) in tourism; where consumers strongly rely on eWOM when selecting a tourism destination, hotel, or restaurant and share their experience with the services encountered during their stay. Verma and Yadav (2021) emphasize the growing interest of practitioners who have started using eWOM to obtain detailed information about their consumers. The improvement of the internet, the popularity of e-commerce, and the widespread use of social media applications have led to the emergence of eWOM. eWOM is based on the concept of oral administration. We can define it as any positive or negative statement of potential, current, or former consumers about a product or business that is available to the wide public and organizations via the internet (Hennig-Thurau, Gwinner, Walsh, & Gremler, 2004). We can also refer to it as to the informal consumer communication via the internet related to the use or characterization of a particular product, service, or business. This communication takes place between companies and consumers, as well as between consumers themselves (Litvin, Goldsmith, & Pan, 2008). eWOM is a source of information on the one hand and a recommendation for others on the other (Park, Lee, & Han, 2007). eWOM distribution channels include blogs, virtual communities, websites, review sites, hate sites, email, chat rooms, instant messages, online discussion forums, and social networks (Chu & Kim, 2011; Litvin et al., 2008).
eWOM has received intensive attention in the available literature for several years. Given the importance of the internet and its impact on consumer behavior, interest in eWOM is expected to continue to grow. As interpersonal interaction is more pronounced in tourism than in other sectors, the impact of eWOM is more accentuated (Abd-Elaziz, Aziz, Khalifa, & Mayouf, 2015). eWOM is considered more credible and reliable than marketing communication created by businesses because eWOM is about views that are drawn from the experience of consumption (Abd-Elaziz et al., 2015; Kim, Li, & Brymer, 2016; Litvin et al., 2008; Pang, 2021).
2.2 Methodology
The literature review was elaborated to systematically review available research studies and academic work and to better understand the current level of knowledge about eWOM. Therefore, this chapter aims to elaborate/develop a review of the literature on the topic of eWOM in the tourism sector. After having set the relevant keywords for the study, the following research question was proposed: What is the current state of eWOM research in the tourism sector? Further research questions evolved: (1) What eWOM activities do the authors focus on? (2) What areas do the authors focus on in eWOM research in tourism? (3) How did the authors collect the data for the survey? (4) Where did the eWOM communication surveys take place? (5) What are the results of the study surveys?
The literature review was conducted from December 2021 to January 2022 using the snowball method. The Science Direct and Google Scholar databases were used to collect eWOM studies in the tourism sector. Keywords were searched in English as follows: eWOM, eWOM in tourism, eWOM and tourism destination, and online review. 56 articles in journals, one paper from a book publication, and three conference papers were found. The publication period of the examined studies was 2008–2021. This chapter provides a clear overview of the undertaken research and classifies them according to set characteristics. First, the focus of eWOM studies on tourism is considered relevant. Second, the examined eWOM determinants (such as volume, information relevance, quality of arguments, etc.) were used to systemize the studies. The studies were then allocated due to the data collection technique used, the survey participants, the geographical location, and the used web pages.
2.3 Results
During the examined period aforementioned (publications published between 2008 and 2021), the authors dealt with the adoption of eWOM, respectively. The impact of reviews on the consumer decision-making process (Abd-Elaziz et al., 2015; Abubakar, Ilkan, Meshall, & Eluwole, 2017; Albarq, 2014; Alsheikh, Abd Aziz, & Alsheikh, 2021; Aprilia & Kusumawati, 2021; Ariyanto & Prihandono, 2018; Arta & Yasa, 2019; Banerjee & Chua, 2019; Bigné, Ruiz, Pérez, & Marti-Parreño, 2020; Chang & Wang, 2019; Dewi & Avicenna, 2018; Deyá-Tortella et al., 2020; Filieri & McLeay, 2013; Jalilvand & Samiei, 2012; Krishnapillai & Ying, 2017; Lim, 2016; Manes & Tchetchik, 2018; Miao, 2015; Mutaqin & Trinanda, 2019; Nechoud, Ghidouche, & Seraphin, 2021; Nieto-García, Muñoz-Gallego, & González-Benito, 2017; Nurhidayati, 2020; Rachmawati, Sieng, & Sabihi, 2021; Reyes-Menendez et al., 2019; Singh & Kathuria, 2019; Sotiriadis & Van Zyl, 2013; Sparks & Browning, 2011; Tapanainen, Dao, & Nguyen, 2021; Vermeulen & Seegers, 2009; Wiwikenanda & Aruan, 2020; Zainal, Harun, & Lily, 2017), providing respectively writing reviews (Bronner & de Hoog, 2011; Cheng & Jin, 2019; Filieri, Galati, & Raguseo, 2021; Geetha, Singha, & Sinha, 2017; Gerdt, Wagner, & Schewe, 2019; Hu & Kim, 2018; Jeong & Jang, 2011; Liu et al., 2021; Nam, Baker, Ahmad, & Goo, 2020; Xu, 2020; Yan, Zhou, & Wu, 2018; Yen & Tang, 2019; Yoo & Gretzel, 2008; Zhou, Qiang, MengLing, & ChuWen, 2019) and to both activities: receiving and providing eWOM (Hernández-Méndez, Muñoz-Leiva, & Sánchez-Fernández, 2015; Kanje, 2020; Lončárić, Ribarić, & Farkaš, 2016; López & Sicilia, 2014).
2.3.1 Prevalent Characteristics of the Examined eWOM Studies From 2008 to 2021
To embrace the nature of eWOM studies, we focused on the type of participants, the geographical location of the research, and the used data collection technique. All reviewed articles and publications used the following research techniques such as questionnaires, interviews, and published reviews on online platforms and managers' responses (Table 2.1). Questionnaires tend to be the most effective way of data collection when examining eWOM.
Forms of Data Collection of the Reviewed Studies.
| Data Collection Techniques | Number of Academic Works | |
|---|---|---|
| Absolute Number | Relative Number (in %) | |
| Questionnaire distributed personally Questionnaire distributed online Questionnaire distributed personally and online In-depth interview Published reviews Published reviews and managers' responses |
17 24 3 2 12 2 |
29 40 5 3 20 3 |
| Total | 60 | 100 |
Source: Authors' Elaboration (2022).
Regarding the background of the participants, they had to have experience with eWOM, and the digital survey, and they had to confirm that they had traveled a certain period before the survey (Table 2.2).
Respondents of Realized Surveys.
| Research Participants | Number of Academic Works | |
|---|---|---|
| Absolute Number | Relative Number (in %) | |
| Tourism destination visitors Hotel guests Restaurant guests Internet platform users Consumers providing reviews Consumers providing reviews and hotel managers University students University students on Mobility Country residents |
8 2 1 11 12 2 4 1 19 |
13 3 2 18 20 3 7 2 32 |
| Total | 60 | 100 |
Source: Authors' Elaboration (2022).
We analyzed the geographical adherence of published articles. Table 2.3 illustrates the number of studies conducted on each continent published between 2008 and 2021. The highest number of eWOM studies was realized in Asia followed by Europe.
The Geographical Location of the Conducted Research.
| Continent | Number of Academic Works | |
|---|---|---|
| Absolute Number | Relative Number (in %) | |
| Africa Americas Australia Asia Europe No country detected |
4 7 1 25 17 6 |
7 12 2 41 28 10 |
| Total | 60 | 100 |
Source: Authors' Elaboration (2022).
When dealing with the issue of eWOM, several determinants played the key role in the analysis. Beside the quality of information, eWOM volume, and its nature, recipient's attitude toward the information, the perceived risk, and the shared values of both contributors and users evoked the interest of academicians (Table 2.4).
Examined Determinants of eWOM.
Source: Authors' Elaboration (2022).
The online reviewers participated in those studies that downloaded already published reviews using web browsers. The published reviews were from the websites listed in Table 2.5, with seven studies from one website, three studies from two, one study from three, and two studies from four. Phillips, Zigan, Santos, and Schegg (2015) used online reviews from 69 online platforms provided by TrustYou. Xie, Zhang, and Zhang (2014) supplemented the reviews' information with quarterly performance information for selected hotels provided by the Texas Comptroller's Office database. Table 2.5 also lists the users of the internet platform who were approached to participate in the surveys. Banerjee and Chua (2019) addressed social network users and Reyes-Menendez et al. (2019) focused on email users. Xiang, Du, Ma, and Fan (2017) compared three major online review platforms: TripAdvisor, Expedia, and Yelp in terms of quality information related to online hotel reviews.
Websites the Authors Focused on Individual Studies.
| Website | Number of Academic Works | |
|---|---|---|
| Online Review Providers | Website Users | |
| Amazon | 1 | 1 |
| Airbnb | 2 | – |
| Booking | 4 | – |
| Ctrip | 2 | – |
| eLong | 1 | – |
| Expedia | 2 | – |
| FourSquare | 1 | – |
| Holidaycheck | 1 | – |
| Hrd | 1 | – |
| Qulatrics | – | 2 |
| TripAdvisor | 3 | 3 |
| 1 | 1 | |
| UrbanSpoon | 1 | – |
| WebCim | – | 1 |
| Yelp | 2 | – |
Source: Authors' Elaboration (2022).
Studies confirm that consumers use eWOM to obtain information about tourism destinations, hotels, restaurants, and other tourism facilities that they want to visit or use and that this information influences their choice (Lončárić et al., 2016; Singh & Kathuria, 2019). Consumers believe that by adopting eWOM, they can reduce the risk of bad service choices and plan their stay more efficiently (Singh & Kathuria, 2019), and consumers rely on easy-to-process information when searching for eWOM (Sparks & Browning, 2011), but also their quality (Filieri & McLeay, 2013). They trust more in posts where the identity of the author is better known (Lončárić et al., 2016; Zainal et al., 2017), and they also place more trust in contributions published on websites designed to evaluate tourism products and services, such as Booking or TripAdvisor (Lončárić et al., 2016). Banerjee and Chua (2019) confirmed in their study that the attractiveness of titles was positively related to trust in eWOM.
As illustrated in Table 2.6 along with the impact of eWOM, the authors also examined the impact of managerial responses on consumer decisions (Mauri & Minazzi, 2013). Chen, Gu, Ye, and Zhu (2019) focused on managerial responses to consumer reviews and their impact on consumer behavior.
The Focus of Studies in the Field of eWOM in Tourism.
| All ourism Services | Tourism Destination | Accommodation Facility | Hospitality Facility | |
|---|---|---|---|---|
| Impact of eWOM on consumer behavior | 3 | 17 | 9 | 2 |
| Impact of eWOM on tourism supply | – | 2 | 4 | 1 |
| Provision of eWOM | 3 | – | 10 | 1 |
| Receiving and providing eWOM | 1 | 3 | – | – |
| Impact of eWOM and managerial responses on consumer behavior | – | – | 1 | – |
| Impact of eWOM and managerial responses on tourism supply | – | – | 1 | – |
| Impact of managerial responses | – | – | 1 | – |
| Comparison of three eWOM platforms | – | – | 1 | – |
Source: Authors' Elaboration (2022).
The authors also examined the impact of eWOM on tourism supply (Kim et al., 2016; Mariani & Visani, 2019; Phillips et al., 2015; Setiawan, Troena, & Armanu, 2014; Susilowati & Sugandini, 2018; Ye, Law, Gu, & Chen, 2011; Öğüt & Taş, 2012) and the impact of eWOM along with managerial responses to tourism supply (Xiang et al., 2017; Xie et al., 2014) compared eWOM platforms.
The researchers have studied the impact of eWOM on consumer behavior in terms of consumption of all tourism services (Sotiriadis & van Zyl, 2013; Singh & Kathuria, 2019; Zainal et al., 2017). Several authors have focused on the decision-making process about the visit to a tourism destination (Albarq, 2014; Alsheikh et al., 2021; Aprilia & Kusumawati, 2021; Ariyanto & Prihandono, 2018; Jalilvand & Samiei, 2012; Krishnapillai & Ying, 2017; Lim, 2016; Miao, 2015; Mutaqin & Trinanda, 2019; Nechoud et al., 2021; Rachmawati et al., 2021; Tapanainen et al., 2021; Wiwikenanda & Aruan, 2020), or on a repeated visit of a tourism destination (Abubakar et al., 2017; Chang & Wang, 2019; Deyá-Tortella et al., 2020) and satisfaction with the tourism destination (Nurhidayati, 2020). In terms of hotel accommodation, the investigated topics have covered hotel selection (Abd-Elaziz et al., 2015; Filieri & McLeay, 2013; Vermeulen & Seegers, 2009), hotel room reservation (Dewi & Avicenna, 2018; Sparks & Browning, 2011), reliability of eWOM about the hotel (Banerjee & Chua, 2019; Reyes-Menendez et al., 2019), reduction of information asymmetry (Manes & Tchetchik, 2018), willingness to pay for the type of accommodation as hotel, apartment, or rural accommodation (Nieto-García et al., 2017). The eWOM and its impact on restaurant selection have been studied recently by Arta and Yasa (2019), and Bigné et al. (2020).
2.3.2 eWOM and Its Impact on Consumer Behavior in Tourism
Furthermore, in addition to the examined determinants of eWOM, various researches uncover the impact of eWOM on consumer behavior and thus consumer response to eWOM. The authors also used the theory of planned behavior (Jalilvand & Samiei, 2012; Miao, 2015), the probability formulation model (Alsheikh et al., 2021; Dewi & Avicenna, 2018; Filieri & McLeay, 2013), the set of reasoning theory to study the influence of eWOM (Vermeulen & Seegers, 2009), and the expectation confirmation theory and the model of consumer decision-making based on hotel attributes (Reyes-Menendez et al., 2019). Tapanainen et al. (2021) developed a model from the Big Five Model and the Information Acquisition Model (IAM) and added the intention to choose a tourism destination, examining the link between eWOM and personality traits and information characteristics of a tourism destination.
Along with the influence of eWOM, they also examined the influence of the image of the tourism destination (Ariyanto & Prihandono, 2018; Nechoud et al., 2021; Wiwikenanda & Aruan, 2020), knowledge of the tourism destination and attitudes of visitors to the tourism destination (Wiwikenanda & Aruan, 2020), the impact of tourism destination trust (Mutaquin & Trinanda, 2019), hotel awareness (Vermeulen & Seegers, 2009), hotel categories, perception of review titles (Banerjee & Chua, 2019), the nature of the product or service provided (Abd-Elaziz et al., 2015; Filieri & McLeay, 2013), and the internal reference price (Nieto-García et al., 2017) for consumer decision-making. The authors also examined the impact of eWOM on tourism destination trust (Abubakar et al., 2017; Mutaquin & Trinanda, 2019), tourism destination image (Aprilia & Kusumawati, 2021), and hotel trust (Sparks & Browning, 2011). Chang and Wang (2019) compared the effects of information from online advertising and eWOM on tourism destination expectations and the resulting satisfaction and revisit intentions. Nurhidayati (2020) focused on examining the relationship between eWOM, quality of service, and tourism destination image and consumer satisfaction in tourism. The authors also researched eWOM on tourism offerings, focusing on the image of the destination tourism, satisfaction, and loyalty of the destination (Setiawan et al., 2014), and online hotel room sales (Öğüt & Taş, 2012; Ye et al., 2011). Phillips et al. (2015) focused on the interactive effects of online reviews on hotel performance attributes, using an artificial neural network model. Susilowati and Sugandini (2018) focused on the relationship of eWOM, traditional WOM, perceived value, and perceived quality to the image of the tourism destination. Mariani and Visani (2019) incorporated eWOM from online travel agencies in measuring hotel efficiency through the Data Envelopment Analysis (DEA). Kim et al. (2016) examined the impact of online reviews on a restaurant's financial performance, with the moderating task being the certification of excellence.
Theorists also discussed the influence of eWOM and management responses on hotel choice by consumers (Mauri & Minazzi, 2013) and hotel performance (Xie et al., 2014), the influence of management responses on future consumer behavior, and subsequent evaluation of their hotels (Chen et al., 2019).
The nature of eWOM represents positive and negative eWOM (Abd-Elaziz et al., 2015; Banerjee & Chua, 2019; Bigné et al., 2020; Dewi & Avicenna, 2018; Mauri & Minazzi, 2013; Nieto-García et al., 2017; Sparks & Browning, 2011; Vermeulen & Seegers, 2009). The volume of eWOM indicates the number of published reviews or posts about a given destination or tourism business (Abd-Elaziz et al., 2015; Lim, 2016; Nieto-García et al., 2017). Information quality eWOM covers usefulness, objectivity, comprehensibility, meaning, accuracy, completeness, relevance, dynamism, timeliness, personalization, diversity, credibility, and added value of information (Abd-Elaziz et al., 2015; Arta & Yasa, 2019; Filieri & McLeay, 2013; Lim, 2016; Mauri & Minazzi, 2013; Nechoud et al., 2021; Reyes-Menendez et al., 2019; Singh & Kathuria, 2019).
The type of review reflects whether the eWOM provider claims on technical attributes using numbers or subjectively interprets the benefits of each attribute to evaluate a product or service (Dewi & Avicenna, 2018). Dewi and Avicenna (2018) also examined the impartiality of eWOM, the consistency of eWOM, the evaluation of eWOM by other consumers, and the validation of eWOM with previous eWOMs, and the visual stimulant. Reyes-Menendez et al. (2019) also focused on the degree of extremism: high number of positive eWOMs and consumer involvement. Sparks and Browning (2011) also examined factors such as the hotel's overall rating. Their study investigated whether positive or negative reviews prevailed and whether consumer reviews emerged/appeared together with the rating in the form of stars.
Yoo and Gretzel (2008) identified important motives to provide online travel reviews and examined differences in motivation based on demographic characteristics. Yan et al. (2018) investigated the impact of consumers' emotional changes on their choice of platforms to provide either positive or negative eWOM. Zhou et al. (2019) examined emotions and their impact on the provision of eWOM together with the choice of the website.
In the case of hotel guests, the authors examined their motivation (Bronner & de Hoog, 2011; Hu & Kim, 2018; Nam et al., 2020) and the emotions arising from the consumption of hotel services and the contribution of eWOM (Geetha et al., 2017; Liu et al., 2021). In addition to examining the motivation for eWOM posting, Bronner and de Hoog (2011) sketched also the consumer profile of the person providing eWOM. Hu and Kim (2018) and Nam et al. (2020) focused on positive and negative eWOM. Hu and Kim (2018) used the personality model The Big Five Model and concentrated on self-improvement, pleasure, altruism, and economic stimuli when writing positive eWOMs, and on ventilating negative feelings, altruisms, and economic stimuli when giving negative eWOMs. Nam et al. (2020) integrated the impact of overall product or service satisfaction, confirmation of expectations associated with previous eWOMs, and personal characteristics of consumers into the research. Yen and Tang (2019) focused on the impact of hotel attributes, along with the previous eWOM experience and the convenience of the platform on which consumers decided to post. Filieri et al. (2021) also examined the impact of hotel attributes on eWOM provision, focusing only on one- or five-star reviews. Their findings were based on expectation confirmation theory and the consumer decision model derived from hotel attributes. Liu et al. (2021) investigated the provision of eWOM on social networks and review sites. Gerdt et al. (2019) examined the extent to which aspects of hotel sustainability play a role in eWOM and consumer satisfaction associated with the sustainable operation of hotels. Cheng and Jin (2019) examined attributes that affect Airbnb users to share eWOM. Xu (2020) compared consumer behavior in providing eWOM focusing on shared accommodation and hotels. When looking closely at hospitality facilities, Jeong and Jang (2011) examined the motivation to write positive eWOM to restaurants.
López and Sicilia (2014) examined the extent to which participation in eWOM can be considered a determinant of eWOM's influence on consumer decision-making in the choice of tourism destination and includes the perceived source credibility. On the one hand, Hernández-Méndez et al. (2015) examined the impact of eWOM on tourism destination selection. Primarily, they focused on the source of information, distribution channels – blogs, social networks, websites of destinations, and sociodemographic characteristics of consumers. Furthermore, their research underlined the willingness of travelers to share their experiences. Lončárić et al. (2016) determined the role and importance of eWOM in the consumer decision-making process. Kanje (2020) addressed the level of consumer participation in the provision and reception of eWOM. Several works confirm that consumers use eWOM to obtain information about tourism destinations, hotels, restaurants, and other tourist facilities that they tend to visit and that this information influences their selection process (Lončárić et al., 2016; Singh & Kathuria, 2019). Consumers believe that the risk of unsatisfactory service benefits may be reduced by the reception of eWOM, and the visit may be planned more efficiently (Singh & Kathuria, 2019); they rely on easy-to-process information when searching for eWOM (Sparks & Browning, 2011), but also their quality. (Filieri & McLeay, 2013). Consumers trust more on contributions with the known identity of eWOM authors (Lončárić et al., 2016; Zainal et al., 2017), and they also contribute to websites designed to evaluate tourism products and services, such as Booking or TripAdvisor (Lončárić et al., 2016). Banerjee and Chua (2019) confirmed in their study that the attractiveness of titles was positively related to trust in eWOM.
The authors have confirmed the significant influence of eWOM on consumer decision-making (Abd-Elaziz et al., 2015; Abubakar et al., 2017; Albarq, 2014; Alsheikh et al., 2021; Aprilia & Kusumawati, 2021; Arta & Yasa, 2019; Bigné et al., 2020; Hérnandez-Méndez et al., 2015; Jalilvand & Samiei, 2012; Jeong & Jang, 2011; Krishnapillai & Ying, 2017; Lim, 2016; Mauri & Minazzi, 2013; Miao, 2015; Mutaquin & Trinanda, 2019; Nechoud et al., 2021; Nieto-García et al., 2017; Rachmawati et al., 2021; Tapanainen et al., 2021; Vermeulen & Seegers, 2009; Wiwikenanda & Aruan, 2020). Furthermore, eWOM also affects destination image, consumer confidence in the destination, perceived resource credibility, consumer satisfaction, and loyalty (Abubakar et al., 2017; Aprilia & Kusumawati, 2021; López & Sicilia, 2014; Mutaquin & Trinanda, 2019; Nurhidayati, 2020; Setiawan et al., 2014; Susilowati & Sugandini, 2018; Wiwikenanda & Aruan, 2020). Jalilvand and Samiei (2012), Mutaquin and Trinanda (2019), Nurhidayati (2020), and Aprilia and Kusumawati (2021) point to the important role of positive eWOM in increasing traffic, building confidence in the destination of tourism, creating a favorable image of the destination tourism, and reducing promotion costs. With their results, Nieto-García et al. (2017) point out that eWOM influences not only the choice and perceived value of eWOM but also the price that consumers are willing to pay. When consumers are exposed to services that generate positive reviews, their willingness increases. If the tourism company causes a positive, or negative impressions, so a large volume of eWOM supports the credibility of consumers, and they are willing to pay more or less than they would pay in the context of a small volume of eWOM. In addition to eWOM, the results confirm that the consumer's internal reference price is an important factor in their willingness to pay for a service or product; as the internal reference price increases, consumers' willingness to pay is growing faster and faster. The more positive the nature of eWOM, the greater the interest of consumers (Mauri & Minazzi, 2013; Vermeulen & Seegers, 2009). On the contrary, Sparks and Browning (2011) argue that consumers are more affected by negative reviews, especially when the overall set of reviews is negative. In addition to the information obtained from eWOM, consumers are influenced by their personality traits, in particular, friendliness, adaptability and imagination (López & Sicilia, 2014; Tapanainen et al., 2021), subjective norm, and perceived behavior control (Jalilvand & Samiei, 2012; Miao, 2015). eWOM has enabled social media users to obtain useful information. The personality of social media users influences whether they perceive eWOM as capable of providing them with useful information and whether they should adopt eWOM and use it in their decision-making (Tapanainen et al., 2021). Consumer perceptions of eWOM are also influenced by their travel experience (Jalilvand & Samiei, 2012) and confidence in the destination of tourism (Abubakar et al., 2017; Mutaquin & Trinanda, 2019). Tourism consumers use official websites of destinations to find information, where they are also allowed to have conversations with each other, followed by travel blogs and social networks focused on travel (Hémandez-Méndez et al., 2015).
Studies show that consumers are influenced by the following factors: (1) rating of recommendations in the form of stars, (2) quality of information, (3) consumer confidence in information, (4) expertise of the eWOM provider, (5) expertise of the eWOM recipient, (6) the volume of eWOM, (7) the nature of the eWOM, (8) the type of website, (9) the recipient's attitude to the information, (10) the perceived risk the consumer may encounter, and (11) the perceived value of the product or service to consumers (Abd-Elaziz et al., 2015; Alsheikh et al., 2021; Arta & Yasa, 2019; Bigné et al., 2020; Dewi & Avicenna, 2018; Filieri & McLeay, 2013; Lim, 2016; López & Sicilia, 2014; Mauri & Minazzi, 2013; Nechoud et al., 2021; Reyes-Menendez et al., 2019; Singh & Kathuria, 2019; Sotiriadis & Van Zyl, 2013; Vermeulen & Seegers, 2009).
Conversely, Ariyanto and Prihandono (2018) argue that eWOM does not have a significant influence on consumers' decisions about visiting a tourism destination, but that the image of the destination has a significant influence. Hémandez-Méndez et al. (2015) argue that WOM from friends, family, and acquaintances influences consumer behavior in tourism to a greater extent than eWOM.
The findings of Ye et al. (2011) show that eWOM has a significant impact on online sales of accommodation services, with a 10% increase in traveler reviews increasing the number of online bookings by more than 5%. Their results emphasize the importance of user-generated online reviews for tourism business performance. Öğüt and Taş (2012) confirm with their results that the higher the consumer rating, the higher the online sales of hotel rooms, but also the price. Positive reviews can contribute to hotel financial performance (Phillips et al., 2015).
Consumer satisfaction generates increased hotel efficiency, but consumer satisfaction is different for two and three-star hotels than for four and five-star hotels. Efficiency assessments generated by DEA models that contain eWOM are radically different compared to assessments derived from DEA models based solely on financial variables (Mariani & Visani, 2019). Banerjee and Chua (2019) also confirm the different perceptions of reviews in different categories of hotels. Mauri and Minazzi (2013) argue that there may be a difference in hotel brands. Known hotel brands could be more resistant to the effects of ratings than unknown brands. Vermeulen and Seegers (2009) argue that the overall impact of online reviews is greater at lesser-known hotels. The volume of eWOM has a significant positive effect on restaurant performance, most notably on net sales, the number of guests, and average control. On the other hand, restaurant performance affects the overall rating of consumers (Kim et al., 2016).
The reactions of managers can significantly influence the subsequent behavior of consumers when deciding on a visit, but also the evaluation of the company. Managerial responses and their impact on the consumer differ in positive and negative reviews (Chen et al., 2019; Mauri & Minazzi, 2013). The overall rating, attribute rating of the purchase value, location and purity, variation and volume of consumer reviews, and the number of management responses are strongly related to hotel performance (Xie et al., 2014). Phillips et al. (2015) think that tourism companies' managers should actively respond to online reviews.
2.3.3 Factors Influencing the Contribution of eWOM and the Motivation to Provide It
Studies on eWOM provision show that consumers share eWOM only with bad or good experiences based on a specific negative or positive threshold of consumer emotions (Liu et al., 2021). Based on their survey, Bronner and de Hoog (2011) can outline the profile of visitors who provide eWOM: (1) more often from the under-55 age group, (2) more often from the high- and lower-middle income groups, and (3) more often from couples, with or without children. Bronner and de Hoog (2011) cite five main categories of motivation in providing eWOM: (1) self-improvement, (2) helping other consumers, (3) social benefits, (4) empowering consumers, and (5) helping businesses. Yoo and Gretzel (2008) confirm that providers of online reviews about tourism services are motivated by helping the tourism service provider, concerns about other consumers, and the need for self-improvement. Ventilation of negative feelings is not considered an important motive. Yen and Tang (2019) argue that the performance of hotel attributes, previous eWOM experience, and the convenience of the platform to which the consumer contributes is the driving force behind providing eWOM about the hotel. Demographic data, accommodation preferences, and economic incentives do not affect eWOM provision. Hu and Kim (2018), Zhou et al. (2019), and Nam et al. (2020) argue that the motivations for providing positive and negative eWOM are different. Hu and Kim (2018) concluded that the biggest stimuli from a positive point of view are self-improvement and enjoyment, and from a negative point of view, they are the ventilation of negative feelings and economic stimuli. The results of Zhou et al. (2019) show that positive eWOM consumers are motivated by sharing experiences, self-improvement, socialization, life recording, expressing emotions, and helping others, and negative eWOMs are motivated by venturing negative emotions, seeking revenge, helping others, and seeking help. Nam et al. (2020) argue that providing positive eWOM consumers motivates altruism, belonging to a particular online community, and the enjoyment of writing reviews. When writing negative reviews, consumers are affected by dissatisfaction with the product or service provided and the inaccurate content of the previous eWOM; they are also affected by altruism and pleasure. The study of Filieri et al. (2021) suggests a moderating role for the hotel category, resp. hotel stars in the relationship between hotel attributes and extreme hotel ratings. The rating of the hotel affects the location of the hotel, the cleanliness of the hotel, the size of the room, and the equipment of the room as a whole, but the price–quality ratio plays a role. With extremely positive reviews, consumers are particularly affected by hospitality, specifically personality and sympathy. For extremely negative reviews, this is the first impression on arrival and registration and the attributes of the bathroom. Among consumer reviews, the total number of extremely negative reviews is less than the number of extremely positive reviews.
Xu (2020) confirms the different consumer behavior in sharing on eWOM about hotels and accommodation in the platform economy. Cheng and Jin (2019) argue that Airbnb consumers generally use the same accommodation attributes associated with hotel stays to assess their experiences. Airbnb users tend to rate their experience based on a reference framework derived from previous hotel stays. When providing eWOM, they are influenced by three key attributes: location, equipment, and host. Price is not identified as a key factor (Cheng & Jin, 2019). Geetha et al. (2017), Manes and Tchetchik (2018), and Gerdt et al. (2019) claim that the reviews differ from the hotel category.
Xiang et al. (2017) assume that reviews vary considerably in quality and in content on different sites. The choice of the type of site where the consumer decides to provide eWOM is influenced by (1) the so-called key factor that interprets how the consumer writes a post or review, whether they write it in the form I enjoyed/did not enjoy my hotel stay, or my hotel stay was amazing/terrible, (2) the nature of the sharing or motivation, whether the consumer wants to attract (3) the importance of sharing can be positive, negative, or neutral, and (4) the audience for which eWOM is intended, whether it is people with whom the consumer has an established relationship or equivalent consumers and service providers (Bronner & de Hoog, 2011; Liu et al., 2021). Consumers share positive eWOM especially on social networks (Liu et al., 2021; Yan et al., 2018; Zhou et al., 2019), and negative eWOM on websites that connect travel communities (Yan et al., 2018; Zhou et al., 2019). Liu et al. (2021) found that consumers share neutral eWOM, which is based on consumption facts, on review sites.
In terms of hotel sustainability, the reviews are presented in a positive context, with consumers mostly interested in food. The authors divided the aspects into four groups: (1) critical, environmentally preferred purchase – food and other products, local producers, buildings and infrastructure, accurate promotion, information and interpretation, employee treatment, energy savings, transport, (2) satisfied – cultural heritage, efficient purchasing/reduction of unnecessary packaging, (3) dissatisfied – water-saving, greenhouse gas emissions, and (4) neutral – biodiversity conservation, compliance, legislation, pollution minimization, sustainability concept, vegetarian/vegan food, allergies, intolerance. Personal interest plays an important role in evaluating hotel sustainability measures during visitors' stay; some sustainability measures reduce the perceived comfort of certain hotel attributes, interfere with maximizing personal benefit, and thus interest, which is important for hotel guest satisfaction (Gerdt et al., 2019).
In hospitality facilities, following elements inspire the guests to write a positive eWOM (1) restaurants' food quality, (2) a concern for others, (3) satisfactory restaurant experiences with service and employees (4) a superior atmosphere in restaurants (Jeong & Jang, 2011).
Positive emotions are more common than negative emotions, and the emotions of men and women are quite different (Yan et al., 2018).
2.4 Conclusion
With the growing interest in the online environment, we suppose that the significance of eWOM communication will also expand. Therefore, it is important to find to what extent it changes consumer decisions and also the activities of tourism companies. This chapter provides a review of the literature of 60 studies that focus on eWOM in tourism. By conducting an overview of the studies, we answered the research questions and thus fulfilled the aim of the chapter. The authors of the examined studies focused on the impact of eWOM, the provision of eWOM, both activities at the same time, and the impact of the management responses. In particular, they focused on consumer behavior (number of studies: 51), and tourism supply (number of studies: 8) and examined the quality of the information provided through eWOM (1 research paper). In reviewed papers, following techniques of data collection were used: questionnaires, interviews, published reviews, and management responses. From geographical point of view, authors from Asia and Europe reflected to pay increased interest into the eWOM research. Consumers use eWOM to obtain information about the tourism destinations, hotels, restaurants, and other tourism facilities they tend to visit. And reciprocally, the information influences their decision-making process. eWOM has a significant impact on consumer behavior, tourism destination, and tourism business performance. The authors noticed that eWOM is perceived differently in different categories and brands of hotels. The reactions of managers can radically influence the subsequent behavior of consumers when deciding on a visit, but also on the evaluation of the company. On the other hand, consumer emotions are decisive in the provision of eWOM, but consumers are also motivated by several factors on which the authors disagree. Motives that influence consumers when writing online reviews include self-improvement, pleasure, altruism, empowerment of consumers, helping tourism companies, sharing experiences, expressing emotions, economic stimuli, previous eWOM experiences, and the reliability of the platform on which they post reviews. The authors disagree on whether consumers are motivated by venturing negative feelings and economic stimuli. As with the reception of eWOM, the hotel category also affects the contribution of eWOM, but there is a visible difference between shared eWOM about hotels and accommodation in the platform economy. Authors also perceive a difference in reviews on different websites, where consumers tend to (1) focus on their feelings in a given situation or describe an event based on facts, (2) draw attention to themselves or want to help others, (3) prefer positive, negative, or the neutral importance of sharing, and (4) reach the consumers for whom eWOM is intended. Consumers will find positive eWOM on social networks, negative eWOM on integrated tourism websites, and neutral eWOM on review sites. Positive reviews are more common than negative ones.
The survey has several limitations, namely, that only two databases were used and the number of studies was limited to 60. Further research and following literature reviews may focus on a larger number of studies or examine only one area or activity, e.g., the impact of eWOM, contribution of eWOM, consumer behavior, or tourism supply. The presented chapter proposes other authors to continue their surveys in this domain in tourism and practitioners to pay higher attention to eWOM.
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- Prelims
- I Introduction
- Chapter 1 Online Reputation Management in Tourism: Emerging Themes, Theories, Problems, and Solutions
- II Determinants of Online Reputation in Tourism
- Chapter 2 The Electronic Word-of-Mouth (eWOM) Focusing Studies on Tourism Research
- Chapter 3 How Have Travelers' Needs Evolved Because of the COVID-19 Pandemic? Corporate Reputation Building in Tourism Industry on Digital Platforms
- Chapter 4 Big Data and Online Reputation Management in Tourism: Leveraging the Role of Entrepreneurship
- Chapter 5 Specifics of Online Reputation Management of Hotel Services Intermediaries and Their Role in Reputation Creation
- Chapter 6 Global Impacts of Online Reputation Management of Pre- and Post-Coronavirus Pandemic: Comparative Analysis in Context of Industry 4.0
- Chapter 7 Factors Affecting the Tourists' Approach to Health and Safety Information in Reviews During the COVID-19 Pandemic
- III Online Reputation Management Strategies
- Chapter 8 How to Boost Reputation in Growing Museums? Evidence From an Italian Case
- Chapter 9 Relevance of Social Media Management in Online Reputation Building in Tourism and Hospitality: Case of Finland
- Chapter 10 Reviews on the Internet Marketing Communication of the SPA Tourism Enterprises in Slovakia
- IV Instruments to Improve ORM in Destination Management
- Chapter 11 Does Tourist Pressure Influence the Online Reputation of a Tourist Attraction? Empirical Evidence From the Uffizi Gallery
- Chapter 12 Triangulating Online Brand Reputation, Brand Image, and Brand Identity: An Interdisciplinary Research Approach to Design the Pathways of Online Branding Strategies in Luxury Hospitality
- Index