ABSTRACT:
This study aims to determine definition of online review in tourism accommodation and elements of online review affecting booking intention. Based on factors derived from previous studies, description and reliability test were used in this study to examine internal impacts of online review on the booking intention of travellers. This study analyzed 248 responses from July to August 2019. The study’s results shows that there are 5 internal elements of online review, namely review from professionals, timing of review, volume, content and review form. This study also analyzes some theories.
Keywords: Online review, accommodation, booking intention.
1. Introduction
From 2010 to 2015, Vietnamese investors have affirmed their position in the market, forming international chain hotels with Vietnamese brand name. In addition to the traditional hotel chain hotels such as Saigon Tourist Corporation known as the brand Saigontourist, or Hanoi Tourism Corporation known as the brand Hanoitourist over the years, there has appeared Vinpearl Hotel chain of Vin Group, hotel chain of collective Sun Group, Muong Thanh hotel chain and so on..., which are highly appreciated by visitors. Vietnamese investors have replaced foreign ones in some high-end hotel projects.
As the result, this leads to certain competition among resort, hotel or homestay services. They have to find the right strategies to not only attract but also keep the potential customers to choose their services. The aims of this paper mainly focus on two things: Firstly, it shows the elements of online review; Secondly, an analysis of attributes influences booking intention. The relative importance of these attributes will thus be identified. The research findings will enhance our understanding of the relationship between hotel reviews and tourists’ booking intention, and help managers to make more accurate decisions when managing reviews.
2. Literature review
Online review: Online reviews are positive and negative reviews of the products which have been sold on the online shopping mall [9]. Several researchers have investigated the impact of hotel reviews on accommodation purchase decisions. Vermeulen & Seegers (2009) found that both positive and negative reviews increase customers’ awareness and improve attitude toward hotels, especially for the less-known hotels. Sparks & Browning (2011) and Coker (2012) found that context and "consideration set" has an impact on booking intentions, trust, and evaluations. Yet, the research designs for previous studies only ask subjects to evaluate one hotel at a time and focus only on how the review content impacts on travelers’ attitudes, without considering other variables.
2.1. Reviewer expertise
Another distinctive feature of online reviews is that they are provided by anonymous individuals [7]. In fact, information sharing is not a genuinely random behavior, as there exists market "mavens" who have a particular propensity to post messages about shopping and the marketplace messages (Feick and Price, 1987). Consumers can identify such market mavens and follow them in the process of making purchasing decisions. As such, the characteristics of communicators, both senders and receivers, play a critical role in information persuasiveness (Dholakia and Sternthal, 1977). More importantly, in the online context, people who made postings tend to search for travel information from others who engage in similar activities (Akehurst, 2009).
2.2. Timeliness of online review
During the information search process, consumers may encounter a large amount of relevant information which is associated with a particular time stamp, which leads to the research concept of timeliness. Timeliness refers to "whether the messages are current, timely, and up-to-date" (Cheung et al., 2008, p. 465). Despite its generally agreed importance, timeliness is frequently ignored in online reviews research (Ives et al., 1983). Madu and Madu (2002) pointed out that a Web site needs to be updated consistently to deliver value-added information to users. Its influence may be even stronger if comments are labeled as "spotlight reviews" because these are shown before other reviews on the comments page [2]. From consumers’ perspective, as time elapses, the average helpfulness of reviews declines (Liu, 2006). In a similar vein, Jindal and Liu (2008) found that in the e-commerce environment, more recent product reviews would get more user attentions.
2.3. Volume of online review
Volume is another important attribute of WOM, and it measures the total amount of interactive messages (Liu, 2006). Variations in the volume of online customer reviews provide evidence that not all hotels are treated equally, and hence, it’s reasonable that not all reviews are treated equally. It has been regarded as a key antecedent of the WOM effect (Bone, 1995). In online settings, volume of reviews is the number of comments from reviewers about a specific product or service (Davis and Khazanchi, 2008). Several studies demonstrate that volume significantly correlates with consumer behaviors like customer-initiated contacts with manufacturers (Bowman and Narayandas, 2001) and market performance in terms of sales (Amblee and Bui, 2007; Liu, 2006; Zhu and Zhang, 2010). Higher volumes of comments, either positive or negative, in online communities are more likely to attract information seekers and then increase product awareness (Davis and Khazanchi, 2008). The number of online comments also signals the level of agreement among consumers (Elliott, 2002).
However, Davis and Khazanchi (2008) argued that an increase in volume of online reviews alone has no significant impact on book sales in e-commerce multiproduct sales. Godes and Mayzlin (2004) reported that the volume of consumer reviews does not have significant explanatory power in terms of weekly box office revenues. Nevertheless, considering the information asymmetry present and the unique features of tourism products such as intangibility and integration of production and consumption (Litvin and Ng, 2001; Taylor, 1980), this study argued that a high volume of online reviews may induce a perception of lowered risk.
2.4. Valence of online review
Message valence focuses on either the positive (benefits gained) or negative (benefits lost) product attributes (Maheswaran and Meyers-Levy, 1990). Online reviews can be either negative or positive within the same location, and impacts of each type have been continuously compared for a better marketing mix. Negative messages are more diagnostic, which implies low-quality products, whereas positive information may be connected to high-, average- and even low-quality products (Herr et al., 1991). As a decision-making process focuses on the message content, consumers place more weight on negative information in making product evaluations (Mizerski, 1982; Richins, 1983; Weinberger and Dillon, 1980). In addition, negative information spreads faster than positive, as angry customers are more likely than satisied ones to tell relatives and friends about their experiences (Hart et al., 1990; Richins, 1983). When the proportion of negative online consumer reviews increases, consumers’ attitudes towards the product would become more unfavorable [7].
The findings of previous work on the effects of message valence are inconsistent. In Maheswaran and Meyers-Levy’s (1990) series of studies, some results indicate that positively framed messages are more persuasive, whereas others suggest the reverse. This lack of consistency may be attributable to the degree to which consumers are involved in detailed message processing. From the perspective of information recipients, Westbrook (1987) showed that both positive and negative information can influence consumers’ loyalty, product evaluation and purchase decision. Therefore, it is more logical to examine the impacts of negative and positive reviews, respectively. Negative comments are mainly generated as a response to dissatisfaction and can be harmful to business retailers and manufacturers by having an adverse effect on business (Charlett et al., 1995). The action of spreading negative information could be even more harmful than simply complaining, which is mostly invisible (Charlett et al., 1995). In contrast to negative comments, positive reviews mainly focus on extolling a company’s quality orientation, such as making recommendations to others (Brown et al., 2005). Positive online reviews are generally recognized as a valuable vehicle for promoting a irm’s products and services (Gremler et al., 2001).
2.5. Form of Reviews
Pictures are formed in the consumers’ first review or additional reviews, which is one part of reviews. The re-views containing pictures reflect the real quality of the goods, such as color problem, specifications inconsistent problem, or the high quality, good experience. The picture reviews reduce consumer’s risk during buying experience goods. In the consumer learning process, picture reviews indicates the real buying behavior. Consumer can complete the comment within 180 days. After that, the seller will give evaluation to the consumer, too.
Cumulative reviews are reviews posted within a month. The reviews may involve color, quality, specification, logistics, customer service and other factors. The reviews can be done a long tirade; also can be a short word evaluation, such as good or bad. Cumulative review is an important channel for consumer to understand goods information before buying. The high richness information can help consumers understand product information deeply. Some study show that the influence of positive reviews replaces the influence of cumulative reviews. But another study found that the quantity of online reviews affect the willingness of consumers to buy on the network. (Zan Mo, Yan-Fei Li, Peng Fan, 2015).
3. Methodology
Online survey was used as a data gathering instrument. Statistical Package for Social Scientists (SPSS) was used to analyze the collected data. The questionnaire was distributed people online in Facebook. The questionnaire was in three sections. Section A gathered information on the behavior frequency. Section B found out the elements of online review while Section C contained demographic data of respondents. The statistical package for social scientists (SPSS 20.0 version) was used in data analysis. The second section of survey consisted of 21 items whose responses varied from 1 (Strongly disagree) to 5 (Strongly Agree) in form of a five point Likert type scale. Out of the total number of 248 copies of questionnaire distributed 248 were retrieved (from July 15th to August 15th) representing 100% response rate which was very much representative of the sample. Respondents are consisted of 248 people (from 10/8/2018 - 28/8/2018) who responded to the online survey accurately. The result of Table 1 has showed that most of the participants were 18 to 25 ages (58.9%) and students (42.7%) and below 2 million income (27.4%). Male is 82 respondents (33.1%) and female is 166 respondents (66.9%).
4. Findings and discussion
According to Table 1, as a result of Reliabilities analysis, six factors namely: Usefulness of online review, reviewer expertise, timeliness of online review, volume of online review, valance of online review, form of online review, with 18 items have Cronbach's Alpha value 0.718, 0.686, 0.627, 0.742 and 0.765. This scale could be considered as a reliable data collection tool within the context of the study.
Table 1. The elements of online review with mean scores
Online reviews are a useful information source for most travelers to generate their intentions and make trip decisions [5]. The present findings demonstrate that impacts of online reviews on travelers’ actions depend on six characteristics/features, including usefulness, reviewer expertise, timeliness, volume, valence and comprehensiveness. These features play identical roles in manipulating traveler intentions and decisions.
Specifically, as for review valence, the current results are consistent with previous findings that negativity effect is more important than other features in predicting consumers’ booking intentions, as Willemsen et al. (2011, p. 31) said that “negativity effect was present only for experience products”. In their study, experience products “are dominated by intangible attributes that cannot be known until purchase and for which performance evaluations can be verified only by sensory experience or booking consumption” (p. 23). In the hotel industry, Ye et al. (2009) suggested that hotels should allocate more resources in managing the valence of reviews, which could lead to increases in bookings/sales. As such, hoteliers may benefit from handling customer complaints more strategically and dealing effectively with service recovery, as at least 5 - 10 per cent of dissatisfied customers choose to complain (Tax and Brown, 2012).
In addition to review valence, comprehensiveness significantly influences people’s online booking intentions. This ending extends previous studies suggesting that people are cognitive misers, as they tend to rely on heuristic cues like easy-to-process graphic information (e.g. numerical or star ratings) to make evaluations or decision (Macrae and Bodenhausen, 2001). Holding a similar stance, Ye et al. (2009) found that hotels with higher star ratings would receive more online bookings. While it is acknowledged that consumers rely on categorical information because it is simple and easy to understand, this study found that comprehensiveness has high predictive power of their booking intentions. A possible explanation for this is the fact that in virtual communities, the mere presence of arguments and anonymity on the Internet lead people to require more cues to judge information based on the rigor of arguments. Also, this study illustrates the positive impacts of timeliness and volume of online reviews on booking intentions. Online reviews are a valuable channel of asynchronous information, which serves as predictive indicators of consumers’ attitudes. At the same time, consumer awareness has been regarded as a key variable in describing consumer choice, which will finally lead to purchase [10]. With more exposure to a hotel brand, there would be a higher chance for consumers to include a hotel into their awareness set. Therefore, more efforts could be devoted to increasing the quantity of online reviews about a hotel.
Furthermore, this study found a positive relation between usefulness of online reviews and online purchase intentions. As mentioned above, consumers are currently in an information overloading situation. This study also found a positive relationship between reviewer expertise and people’s booking intentions. This is consistent with previous studies discussing effects of source expertise upon respondents’ perceptions (Tan et al., 2008). Biswas et al. (2000) suggested that expertise refers to relevant intelligence to the object of discussion and a reviewer needs to possess knowledge on a specific topic. In the hotel industry, this expertise includes good reputation, greater hotel knowledge and good credit record, all of which are typical features of opinion leadership (Bloch et al., 1989). Opinion leaders are individuals who can influence the opinions and behaviors of others positively and frequently (Jamrozy et al., 1996). Jamrozy et al. (1996) empirically examined the relationship between involvement and opinion leadership in tourism and suggested that opinion leaders are identifiable. It would, therefore, benefit hotels to seek out and obtain more specific information about opinion leaders, such as how they diffuse their personal experiences of consuming hotel products and services.
5. Conclusion, research limitations and implications
The research has discovered 5 elements of the online review that influence the booking intention such as reviewer expertise, timeliness, volume, valance, form of online review.
This study’s limitations provide directions for future study. One of the major findings is that the interrelationships among features of online reviews, which were discussed in other similar studies, were not considered. As such, it would be worthwhile for tourism scholars and practitioners to empirically examine different information channels to optimize their promotional efforts and adjust the resources allocation accordingly. Further, future work could compare the impact of online reviews across different tourism sectors. While the current study focused on hotels only, the results may be applicable to other market segments. For example, it is reasonable to suggest that online reviews may have a greater influence on products that are more likely to be purchased online (such as light tickets) than on those sold mainly offline (such as entrance tickets for scenic spots). The orientation of future research is to determine the effect of these factors on the booking intention through the regression anal and to compare the level of influence between different tourist groups.
This research is funded by University of Economics under the University of Danang
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NGHIÊN CỨU VỀ ĐÁNH GIÁ TRỰC TUYẾN
ĐỐI VỚI DỊCH VỤ LƯU TRÚ DU LỊCH
● ThS. NGUYỄN CAO LIÊN PHƯỚC
Giảng viên Trường Đại học Kinh tế - Đại học Đà Nẵng
TÓM TẮT:
Nghiên cứu nhằm khái niệm cụ thể về đánh giá trực tuyến trong lĩnh vực lưu trú du lịch và các thành tố của đánh giá trực tuyến ảnh hưởng đến ý định đặt phòng. Từ các yếu tố tổng hợp được qua các nghiên cứu trước đây, nghiên cứu này sử dụng kỹ thuật phân tích nhân tố, độ tin cậy (reliability analysis) để xác định các yếu tố nội tại của đánh giá trực tuyến có ảnh hưởng đến ý định đặt phòng của khách du lịch. Kết quả nghiên cứu được phân tích dựa trên 248 phản hồi từ tháng 7 và tháng 8 năm 2019. Kết quả cho thấy, tồn tại 5 yếu tố nội tại thuộc đánh giá trực tuyến, là: chuyên gia đánh giá, thời gian của đánh giá, khối lượng, nội dung và hình thức đánh giá. Một số lý thuyết khác cũng được thảo luận trong nghiên cứu này.
Từ khóa: Đánh giá trực tuyến, lưu trú, ý định đặt chỗ.
