I would like to express my sincere thanks to the many people who made this theme possible. Randall Shannon, Ph.D., my advisor, for his extensive support and valuable advice regarding all aspects of this study. The aim of this study was to find the key factor influencing customers' dependence on e-WOM in the hotel industry.
The result of this research will present three factors that influence the e-WOM customers' trust before making a hotel reservation, such as uncertainty reduction, volume of online reviews, and value of online reviews. Most people trust a large number of positive reviews and at the same time weight the information with negative reviews if there are conflicting comments. Nowadays, most of the pre-purchase buyers check reviews, ratings and comments online before making a purchase decision.
Consumers have different criteria. Therefore, to gain more certainty and confidence, many customers seek information by checking online customer reviews, e-WOM and ratings before booking a hotel they have never experienced before. The core question of this research is “How the e-WOM factor (electronic word of mouth) can have a major impact on the hotel sector”. This research objective is to study and understand the factors that persuade customers' trust in e-WOM when making a decision to book the hotel, and how they measure and weigh positive and negative reviews.
This research will be conducted in domestic (Thailand) by focusing only people who have previous experience in hotel booking.
LITERATURE REVIEW
Theoretical Foundation
- Uncertainty reduction theory
- Word of mouth (WOM) and Electronic word of mouth (e-WOM) communication
- Consumer perceptions of online consumer reviews
- Volume of online reviews
- Valence of online reviews
Thereby, collecting information from online reviews can be used to reduce the uncertainty (eg read online customer review from the online travel agent website) to see previous customers who have experienced and shared their opinions on the online website. At the same time, however, uncertainty can be increased if there is also conflicting information. Consumer perception of online consumer review is how the readers think and perceive after gathering the information they need.
The consumer reviews provide full information about products or services that can be used in decision making (Chatterjee, 2001; Clemons et al., 2006). These days, the online site becomes an important channel to get related product and service information (Bounie et al., 2005), it is consistent with the model proposed by Schmidt and Spreng 1996). Variations in the volume of online customer reviews show that not all hotels are treated equally, and therefore it stands to reason that not all reviews are treated equally.
Online review valence is either the positive or negative aspects of what the consumer thinks about the product/service. It can be either of these two aspects equally and the effects of each type have been compared for a better marketing mix. Negative messages are more diagnostic of the defective product/service, implying low quality, whereas positive information can be associated with high, average, and even low quality products (Herr et al., 1991).
In general, negative opinion spreads faster than positive, as angry customers are more likely than satisfied customers to tell peers about their experiences (Hart et al., 1990; Richins, 1983). When the numbers of negative online consumer reviews become higher, consumers' attitude towards the product will become more unfavorable (Lee et al., 2008). Negative comments mainly focus on dissatisfaction which can be harmful to business (Charlett et al., 1995).
In contrast to negative comments, positive reviews mainly focus on praising a company's quality direction, such as making good words to others (Brown et al., 2005). Especially in experiential service, customer recommendations and good words can be persuasive enough to persuade. Through these strong positive ratings, it can also lead to a significant sales growth for business, according to Clemons et al.
Hypotheses Development
RESEARCH METHODOLOGY
- Research Design
- Data Collection Methodology
- Population and Sample
- Data Collection
- Instrument
- Data analysis
It will start with online hotel booking, whether the respondents have experienced this platform or not, how much they trust online reviews. Then the questionnaire will link them with a more detailed question to gather the amount of consumer perception of the factors of online reviews, such as the scope and value of them. A questionnaire will be carried out, an analysis will be carried out and part of these will be used for the presentation.
Frequency Analysis: This analysis is a simple method to show the result of the data collection as a percentage of each factor and customer perception of e-WOM.
FINDING AND DISCUSSION
- Sample Characteristics
- Percentage of Demographic Factors
- Descriptive Statistics
- Customers who checking the online customer reviews before doing hotel booking
- Factor that affect customers’ attitudes toward hotel booking The factor that affect respondents’ attitudes toward hotel booking were shown
- Perception of customer toward online customer reviews
- Discussion
The final samples have a gender split of 68 males or 51.1 percent of the total sample and 65 females or 48.9 percent of the total sample. Regarding education, 58.6 percent have a Bachelor's degree, 27.8 percent have graduated with a Master's degree, and 11.3 percent have graduated from a vocational school. Respondents frequently check online customer reviews before booking a hotel, with the majority of respondents (91.7 percent) followed by 8.3 percent who do not.
For the chance of respondents who are likely to book the hotel they have never experienced before, the most 48.1 percent are likely to book the hotel, 27.8. There are 64.7 percent which is the highest number with Agree followed by 25.6 percent who strongly agree and 9 percent of disagree to check e-WOM before booking the hotel. Third, Online customer reviews averaged 2.9, the average as was the hotel's advertising and loyalty program of credit card or hotel, respectively.
From the questionnaires, the next section is the result of customer perception against online customer reviews. Figure 4.5 shows that customers' perception towards booking the hotel was more confident that they would check the online customer reviews first. Most respondents (43.6 percent) strongly agree, followed by 42.1 percent who agree and 14.3 percent who disagree.
Based on the number of positive reviews, most of the respondents agreed that they were more interested in the hotel they had never experienced before if there were numbers or the positive number such as 49.6 percent. According to figure 4.8, the respondents' opinion is to compare both negative and positive e-WOM. Most of the respondents strongly agreed that the amount of negative e-WOM influenced their attitude towards this hotel, as 53.4 percent and 36.1 percent agreed.
Therefore, to get more information about that particular hotel, people check online customer reviews such as stars, ratings, and reviews. In addition, from table 4.7 which shows us about "Factors influencing customer's hotel booking attitude", Price is the highest average with 3.2, but most of the respondents also rate Reliability, Online Review and Travel Blog with respectively 3.15, 2.9 and 2.79. which may be involved in consumer uncertainty and consumer perception of online review theory. Second, this research found that higher volumes of comments can influence respondents, either positively or negatively, such as Figure 4.9 “Impact of volume on customer decision-making” The majority of respondents strongly agree as 43.6 percent, followed by of which 42.1 percent agreed and Figure 4.10 “Positive e-WOM numbers could be more interesting” 49.6 percent agreed.
Third, there were similar results that the valence of online customer reviews could affect customers, especially the amount of negative web pages could be more attractive to customers, as shown in Figure 4.11 and Figure 4.12. According to Figure 4.10, the number of positive e-WOM can lead to more interesting ones, the majority of respondents agreed, namely 49.6 percent.
CONCLUSION
Be honest with your customers and let them know that you want their feedback to improve your hospitality business, because in this age of social media, they understand that easily. A limitation of this research is that the number of respondents is too low, as 133, so it was difficult to link individual data for comparison. For example, a comparison for ANOVA or a crosstab to see related variables and factors.
The researcher recommends readers who are willing to do research in this area to distribute more questionnaires and be more specific with the question in order to get more accurate answers. In the last part of this chapter, the researcher hopes that this research will be useful for readers to understand how important the perception of e-WOM is able to influence the hotel business in this era of social media. Once customers perceive the bad attitude or the volume of negativity from the review site, it is difficult to recover your brands.
Just doing the best marketing, trying to increase sales with advertising may not be enough these days.
EXTERNAL INTERNAL
APPENDICES
Appendix A: Questionnaire Question
