THESIS MARKETING
MSc Business Studies – Marketing Track
“What Makes Online Reviews More Influential on Consumer
Purchase Attitudes and Behavior in Travel Industry”
Full Name : Archi Swasti Soetoyo Student Number : 10840966
Date of Submission : 29 June 2015 – Final Version Under Supervision : Dr. Umut Konuş
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STATEMENT OF ORIGINALITY
This document is written by Archi Swasti Soetoyo who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in
creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
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ABSTRACT
The existence of online travel communities makes peers-generated recommendations increasingly available in online environment. This phenomenon drives a considerable change in consumer’s decision making process. Accordingly, in the context of hotel booking website, this research aims to analyze some of the key elements of online reviews including; (1) message positivity, (2) number of reviews and (3) platform reputation that influencing customer’s intention to adopt the information. By using a 2 x 2 x 2 experiment study (N=221), the result indicates that the number of reviews is the most influential factors that triggers customers intention to follow peers’ recommendation. Furthermore, when considering customer’s characteristics, customer’s expertise shows a moderating effect on the relationship between message positivity and information adoption, even though the level of positivity have no significant effect. Based on these findings, some practical implications are widely discussed and contributed to marketing studies in online market environment.
4 Table of Contents STATEMENT OF ORIGINALITY ...…………..……….. 2 ABSTRACT ……….………. 3 TABLE OF CONTENTS ………..……….. 4 CHAPTER 1 - INTRODUCTION 1.1 Research Background………... 7 1.2 Research Structure…... 10
CHAPTER 2 - LITERATURE REVIEW 2.1 Word-of-Mouth (WOM) …...………..…………... 11
2.2 Electronic Word-of-Mouth (eWOM) Communication ……...… 12
2.3 eWOM Activities in Online Environment ………... 13
2.4 Online Review ……….. 14
2.4.1 Online Review Elements: Messages positivity ……...…... 16
2.4.2 Online Review Elements: Number of Reviews ... 18
2.4.3 Sources: Website’s Credibility... 19
2.5 Message Contents …………...………. 21
2.6 Information Adoption ...………. 22
2.7 External Factors: Demographic Characteristics ………..………... 23
2.8 External Factors: Psychographic Characteristics …...………..………….. 24
2.9 Factors Affecting The Online Travel Behavior ……… 25
2.9.1 Travel Online Community………..………. 27
2.10 Literature Gap ………...…………..…29
2.11 Theoretical Contribution ………. 30
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CHAPTER 3 - CONCEPTUAL FRAMEWORK AND HYPOTHESES
3.1 Research Framework ……….. 31
3.2 The Influence of Message Elements on Intention to Adopt Information ……… 32
3.3 The Influence of Website’s credibility as Source on Intention to Adopt Information ……. 33
3.4 Moderating Effects of Customers’ Demographic Characteristics ….……….. 33
3.5 Moderating Effects of Customers’ Psychographic Characteristics ……….. 34
CHAPTER 4 - RESEARCH DESIGN AND METHODOLOGY 4.1 Research Design ………..………..… 37
4.1.1 Treatment Object ………... 37
4.2 Experimental Design………..…….… 38
4.2.1 Pilot Test and Questionnaire Structure ……… 39
4.2.2 Variable Measurements ………... 40
CHAPTER 5 - RESULT AND ANALYSIS 5.1 Data Collection and Sample Characteristics ……… 43
5.2 Data Preparation and Manipulations Check ……….. 44
5.3 Hypothesis Testing ……… 46
CHAPTER 6 - DISCUSSION AND CONCLUSION 6.1 Discussion ……… 51
6.2 Managerial Implication ………. 54
6.3 Limitation and Suggestions for Further Research ……….. 56
REFERENCES ……….………. 57
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Figure List
Figure 1 Global Trust in Advertising Survey ….……… 7
Figure 2 eWOM Activities ……….. 13
Figure 3 Conceptual Frameworks by the Author ……….. 31
Figure 4 Factorial Design for Credible and Incredible Review Site ……… 38
Figure 5 Estimated Marginal Means of Information Adoption ……… 49
Table List Table 1 Theoretical Foundations of Prior eWOM Literatures ……….……… 15
Table 2 Key Elements Associated with Information Process in Online Context ………. 27
Table 3 Treatment Validity Check ……….. 43
Table 4 Means, standard deviations, correlations and reliabilities per variable …….. 45
Table 5 ANOVA: Test between Subjects Effects (Information Adoption) ………. 48
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CHAPTER 1 INTRODUCTION 1.1 Research Background
Over the last couples of years, there is a significant change on consumer buying behavior because they can easily access and obtain information from the Internet (Nielsen Company, 2012). The development of Web 2.0 allows consumers to engaging each other through blogs, ratings and reviews, tagging and other interactive forums before, during and after a purchase (Mooney & Rollins, 2010). A survey in United State reveals that almost 90 percent of consumers are influenced by online reviews in their buying decision (Gesenhues, 2013) and most of them perceive online consumer-generated reviews as a credible and unbiased source of information compare to other sources (Casaló, Flavián, & Guinalíu, 2011). Moreover, as illustrated by Figure 1, online consumer reviews also became the second most reliable source after recommendation from friends or relatives and the numbers of global consumers who trust these messages are also growing by 15 percent in last four years (Nielsen Company, 2012).
Figure 1 Global trust in advertising survey (Nielsen Company, 2012).
besides that, some studies argue that online reviews are influencing customer’s decision making more significantly for experiential goods such as destinations, hotels, or restaurants because customer find it difficult to assess services quality prior to the consumption (Z. Liu & Park, 2015). That is why almost 50% of travelers visited online forum
8 or online community to obtain information before purchasing the products and 40% of them subsequently purchase the products (Z. Liu & Park, 2015; K. Z. Zhang, Lee, & Zhao, 2010). This phenomenon brings online reviews to a more serious consideration for both marketing practitioners and researchers in the area of travel products. It is not only because this kind of resources are more reliable but also because of the low searching cost (Z. Liu & Park, 2015).
On the one hand, such reviews provide a profitable and customer-centric marketing tactics for travel businesses because the exposure of quality information could reduce the price sensitivity for certain hotel or restaurant without spends big amount of marketing budget (Freedman, 2008; Vermeulen & Seegers, 2009). But on the other hand, the growing numbers of online communities namely TripAdvisor, Airbnb, and Booking.com contribute to the lack of companies’ control over their brand message (Casaló et al., 2011; eMarketers, 2013). It is also makes branding become less importance and makes the competition tougher because newcomers have relatively low barriers to entry (Simonson & Rosen, 2014). Additionally, rather than trying to understand consumer’s behavior towards their subsequent adoption, some marketers only focus on traditional measurement regarding consumer-generated reviews (Freedman, 2008).
Even if many scholars have investigated the impact of electronic messages to consumer buying behavior, such as intention to purchase the reviewed product and service (Duan, Gu, & Whinston, 2008; D. Park & Lee, 2008; Zhu & Zhang, 2010), there is still a gap in between the line. There are only limited sources that examine the degree to which customers willing to adopt the customer-generated online reviews for their purchase decision and taking external factors into account. Whereas, by finding out these matters,
9 marketers will be able to influence the formation which is useful for consumer consideration, and improve hotel awareness (Jiménez & Mendoza, 2013; Vermeulen & Seegers, 2009). Moreover, since comScore (2007) reveals that 84% review users were more influenced by recommendation from fellow customers rather than professionals-generated information, customer-generated reviews consider as more objective and unbiased information for them (Casaló et al., 2011).
In this vein, some other researches start to examine the impact of online reviews on customer behavior and found out that it is depends on numbers of different factors, such as; message nature and quality (Chevalier & Mayzlin, 2006; Vermeulen & Seegers, 2009; K. Z. Zhang, Hu, & Zhao, 2014), the type of products (Jiménez & Mendoza, 2013; Ling & Yazdanifard, 2014) and the characteristics of the readers (C. Cheung, Xiao, & Liu, 2012). Thus, by considering the previous researches this study focuses on the key elements of online reviews including message valence, reviews volume and the platform reputation in order to predict customer intention to follow the advices. Furthermore, the external factors such as customer’s characteristics also taken into account.
In addition, by examining the precursors of consumer behavior in online environment, this research contributes to the study of online travel industry as the influence of peers-generated information has been dominated the buying decision in this sector (Simonson & Rosen, 2014). Moreover, due to a considerable growth of platforms where travelers can exchange information (Casaló et al., 2011; Z. Zhang, Ye, Law, & Li, 2010), companies can at least have control over their message. Theoretically, it provides an insight regarding the antecedences of customers’ decisions making process in online environment as well as other factors that may influence this process. For travel business perspective, this
10 research also gives more complete information to assures potential buyers, who already has access to most of the competitors' offers, and provides relevant recommendations to understand online market situation.
1.2 Research Structure
To fully understand the theoretical background about online review, secondary data were collected from prior literatures regarding online communication such as electronic word-of-mouth and the customers’ information process in online context. In Chapter, those related studies will be discussed and constructed to determine the gap in the existing literatures. From the existing knowledge that has been found, conceptual framework developed to illustrate the relationship among variables that formulated into research hypotheses that will be explained in Chapter 3. In Chapter 4, research strategies and methodology will be designed in order to test the hypotheses and analyze the collected data. The results of this research are elaborately explained in Chapter 5. Finally, the result conclusion will be drawn to addressing the research questions in Chapter 6, along with research limitation and managerial implication.
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CHAPTER 2 LITERATURE REVIEW 2.1 Word-of-Mouth (WOM)
Hennig-Thurau, Walsh, & Walsh (2003) considered word-of-mouth communication as a key element of consumer behavior which is defined as "all informal communications directed at other consumers about the ownership, usage, or characteristics of particular goods and services or their sellers" (Hennig-Thurau, Walsh, & Walsh, 2003). Other researchers have also demonstrated that not only consumer’s choice and purchase decision that influenced by information exchange among customers, but also the formation of their expectations, pre-usage attitudes, and even post-usage perceptions of a product or service (Jalilvand, Esfahani, & Samiei, 2011). Since long time ago, WOM has been regarded as an important external source of information because it reduces the level of risk and uncertainty toward the products. The recommendations from relatives or even experts also effectively influence the traveler’s service selection such as hotels and restaurants while formal media (e.g. guide books and advertisement) only has limited effects on their decision (Z. Zhang et al., 2010).
However, a study by Kaisheng (2010) mentioned that WOM communication is not always effective for every type of products, or at least it cannot reaches what marketers want to achieve. This might occur due to in traditional WOM communication the exchange of information mainly happened in private conversations which has limit direct observation by the customers (Jalilvand et al., 2011). Although internet development has overcome this limitation, many businesses are also considering the importance of offline sources to attract consumers even they purchase the product through the Internet (Cheema & Papatla, 2010).
12 Therefore, there are certain ways needed for companies in using online information in order to achieve their marketing goals.
2.2 Electronic Word-of-Mouth (eWOM) Communication
The rapid growth of Web 2.0 brings a new form of communication vehicle that extending traditional WOM to electronic WOM which eliminating consumers’ uncertainty by allowing them observe the product directly (Jalilvand et al., 2011). According to Hennig-Thurau et al., (2003) electronic Word-of-Mouth (eWOM) is “any positive or negative statement made by potential, actual, or former customers about a product or company, which is made available to a multitude of people and institutions via the Internet” (Jalilvand et al., 2011). EWOM has three dimensions of uniqueness that differ it with traditional WOM (C. M. K. Cheung & Thadani, 2012).
First, it is possess unprecedented scalability and speed of diffusion communications which involve multi-way exchanges.
Second, eWOM communications are more persistent and accessible. It is archived in the cyberspace and available for an indefinite period of time.
Third, communications are easier to measure and observable than traditional WOM.
Furthermore, numbers of literatures have identified some types of eWOM in online environment namely; online discussion forum, online review sites, blogs, social networking sites, online shopping sites (C. M. K. Cheung & Thadani, 2012). These various types of online communication platforms are able to influence consumers’ information adoption (Subramani & Rajagopalan, 2003) which being used within the decision making process (Casaló et al., 2011). Consequently, consumer’s activities in purchase decision become more complicated than before (Jalilvand et al., 2011).
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2.3 eWOM Activities in Online Environment
The main difference between traditional and electronic WOM is on the platform through which consumers exchange their information and changing their activities (Z. Liu & Park, 2015). As illustrated by Lee & Lee (2009) in Figure 2, there are three major parts needed in explaining eWOM activities that are; product information abstract process, product information inference process, and decision making process. From this model, market-level focus on the effect of eWOM messages to market parameters such as product sales, while individual-level research more focus on how its information affects customer’s decision-making process (C. M. K. Cheung & Thadani, 2012; Lee & Lee, 2009). Applying the same approach, this research will also focus on product information inference process when a customer uses eWOM system in the travel industry.
Figure 2 eWOM activities (Lee & Lee, 2009)
In regards to information process, the explosion of information availability in travel sector enables customer to spend lower costs and efforts in reducing their perceived uncertainty during decision making process (Z. Liu & Park, 2015). This leads to a growing importance of online reviews studies in customers’ purchase decision for such industry (Z. Liu & Park, 2015; Vermeulen & Seegers, 2009; Z. Zhang et al., 2010). Since customers are more depend on peer review because they perceived it as more reliable and sufficient than
14 other sources (Casaló et al., 2011; Z. Liu & Park, 2015), it becomes a new element in social communication process (C. M. K. Cheung & Thadani, 2012).
2.4 Online Review
Customers’ review act as a specific type of eWOM that can be defined as peer-generated product evaluations which impacting consumer buying decision process (Jalilvand et al., 2011; Mudambi & Schuff, 2010). Generally, online reviews consist of graphical and textual elements that allow customers to assess and determine the usefulness of the information for their purchase decision (Jiménez & Mendoza, 2013). Such reviews made on e-commerce websites, discussion forums or rating sites, where some of the platforms allow readers to vote on whether the information is useful for their decision process (Z. Liu & Park, 2015). Aside from search product, consumer review for experience products such as travel services, have been highlighted in prior literatures because it is harder to evaluate the quality before the consumption (Casaló et al., 2011; Gretzel & Yoo, 2008; Vermeulen & Seegers, 2009; Z. Zhang et al., 2010).
Furthermore, by allowing consumers to post their product or service evaluations, the seller creates a new information channel for consumers that provide two distinct roles; give information and serves as a recommendation (Chen & Xie, 2008; Gretzel & Yoo, 2008). These roles are motivating deep changes in consumer decision making process since consumer-generated reviews are perceived as more objective information sources (Casaló et al., 2011). However, for the role of information provider customer tends to focus on peripheral cues, while for recommendation role customers use central cues to evaluate the alternatives (Z. Liu & Park, 2015).
In addition, regarding the impact on consumer intention behavior, numbers of prior literatures have considered online reviews as a part of eWOM which significantly influences
15 this behavior. Based on these literatures there are some precursors which contribute to consumer information process and buying behavior. Thus, table 1 summarized previous literatures about the effect of eWOM and online reviews on people behavioral intention underlying the idea of this research.
Table 1 Theoretical Foundations of Prior eWOM Literatures
Authors (published year) Key Findings
(Hennig-Thurau et al., 2003) The motivation of online message articulation; save decision making time and make better buying decisions which influence their behavior. Jalilvand, et al. (2011) The description of online interpersonal influence along with challenges
and opportunities in eWOM context.
Cheung & Thadani (2012) Integrative conceptual framework in the area of eWOM communication based on provided literatures.
Casaló et al. (2011) The antecedences of information adoption in travel industry; Trust and usefulness of information.
Lee & Lee (2009) Developed customer purchase intention model (quality and preference as antecedents) and illustrated eWOM level within it.
Liu & Park (2015) Factors that affect information usefulness in travel industry; messenger and message characteristics which qualitative aspect identified as the most influential.
Vermeulen & Seegers (2008)
Message valence of reviews (negative & Positive) increase consumer awareness while positive reviews gain attitude toward objects (hotel). Hotel familiarity moderates these effects.
Sussman & Siegal (2003) Theoretical model of information adoption with information usefulness as a mediator of the influence process.
Jiminiez & Mendosa (2013)
Positive effect of reviews credibility as a result from message detail and agreement on purchase intention. Moderating effect from product type.
Chevalier (2006) Greater effect of negative online reviews on sales than positive reviews Cheung et al. (2008) The impact of information usefulness on information adoption and significant precursors of this relationships in online communities
16 Due to the proliferation of online reviews system, a better understanding on its elements become more important in predicting customer’s information process. By using four elements from Hovland’s social communication process (C. M. K. Cheung & Thadani, 2012) this study will investigate the stimuli, sources, response, and also receiver’s characteristics. Here, online review will form new communication stimulus by involving its characteristics which are message positivity and review volume. In addition, the credibility of review platform also considered as one key factors of predicting message adoption.
2.4.1 Online Review Elements: Messages positivity
Messages valence has been considered as one of the review elements that effecting consumer’s response to eWOM (C. M. K. Cheung & Thadani, 2012; Chevalier & Mayzlin, 2006; D. Park & Lee, 2008). In this matter, message with positive direction emphasizes the strength that persuades reader to adopt the product or service. While, negatively framed message will highlights the weakness and discourage readers to adopt particular product or service (C. M. K. Cheung & Thadani, 2012). Numbers of studies in the travel sectors also discuss the numerical ratings, which indicate direction for consumers’ assessment of the travel services which positively influence the perceived usefulness of the reviews (Chevalier & Mayzlin, 2006; Z. Liu & Park, 2015).
Furthermore, most of the literatures show that positive and negative framed word-of-mouth has an asymmetric impact on returns (Tirunillai & Tellis, 2012). Negatively framed reviews have greater impact than the positive when consumers have less cognitive knowledge about the product (C. Park & Lee, 2009). Former researches also find similar consequences of message valance to eWOM effect in
17 search product such as book online market where ratings become a significant influence for product sales in the book market (Chevalier & Mayzlin, 2006). In these studies, it is believed that customers’ information process are influenced by the higher perceived diagnosticity of negative information which give it more weight than positive information (Tirunillai & Tellis, 2012). Thereby, the eWOM effects which appear to be asymmetrical in negative eWOM have stronger reaction on customers' brand evaluations and on the purchase intentions than a positive WOM (C. Park & Lee, 2009). However, Wu, Van der Heijden, & Korfiatis (2011) argue that readers’ attention that generated by the negative framed messages still could not guarantee the usefulness of the information. This is because positive reviews have a much larger impact on consumer behavior than their negative reviews which influence their product or service selection (Forman, Ghose, & Wiesenfeld, 2008; Vermeulen & Seegers, 2009). Therefore, maintaining positive framed messages in online retail platform are important to increase the usefulness of the information.
In the context of message direction, the effect of positivity level to information helpfulness brings more interesting fact, which extreme high or extreme low evaluations are more influential than the moderate evaluations (Mudambi & Schuff, 2010). Extreme cues are perceived as less ambiguous and more salient than cues of moderate value that helps readers’ make purchase decision. Moreover, extremely positive judgment towards product or service provides useful insight (Forman et al., 2008; Gershoff, Mukherjee, & Mukhopadhyay, 2003). Moderate evaluation, in contrast, proved to be less helpful and more ambiguous than the extreme evaluation (Forman et al., 2008). Although some literatures in online context find that consumers have higher judgment toward moderately favorable
18 rating, it was only occur when the review consists of two sided messages (pros and cons)(Schlosser, 2011). Since several evidences have been found, the analysis of extremity effects to intention to adopt information in the online context may be useful to understand travelers’ behavior.
Nevertheless, aside from the level of message extremity, external factors such as customer commitment to the reviewed brand have been proved to moderate the processing of negative information (Ahluwalia, Burnkrant, & Unnava, 2000). Customers who are committed to the brand can easily resist the negative information and induce switching behavior than those with low level of commitment. Therefore, based on previous research by Ahluwalia, et al (2000), in order to overcome the negative publicity, they suggested marketers to attempt two types of response strategy. Meanwhile, diagnosticity strategy is suitable for those who committed to the brand and counterarguments strategy for customer with low commitment toward the brand. However, this finding only valid when brand of reviewed product or service is taken into account.
2.4.2 Online Review Elements: Number of Reviews
Numbers of studies have also found a relationship between the number of consumer reviews and perceived quality of the information. Number of reviews or review volume measures the total amount of posted reviews or comments from reviewers about a specific product or service (C. M. K. Cheung & Thadani, 2012; A. Davis & Khazanchi, 2008). Evidences have shown that the more reviews available in online environment regarding certain product or service leads to an increase in
19 perceived usefulness of the information for customers’ decision (Gretzel & Yoo, 2008).
Even though reviews volume received the same attention as message direction in the context of eWOM effect, a considerable number of literatures found that volume of reviews is more associated with consumer buying behavior (C. M. K. Cheung & Thadani, 2012). This is presumably because the overall online consumer reviews and positive reviews can generate awareness as well as form positive attitude toward product or service (Vermeulen & Seegers, 2009). Even negative reviews can increase likelihood of purchase (Berger, Sorensen, & Rasmussen, 2010). This notion is also supporting Duan, Gu and Whinston (2008) who argue that the number online posting can give a signal of product popularity with variety of its information (D. Park & Lee, 2008).
Not only for search products, the information usefulness for experience products also depended on the number of reviews. For example, according to Liu (2006), review volume is more significantly influence consumer behavior toward movies and the movie revenue rather than message valence. By this fact, firms should be conscious about rumors especially eWOM, since it influences speculation toward the movie. Furthermore, the volume of eWOM offers significant explanatory power for box office revenue in general, through an informative effect on awareness both in short term and long term (Y. Liu, 2006; Tirunillai & Tellis, 2012).
2.4.3 Sources: Website’s Credibility
In the context of eWOM, people exchange experiences and information through online platform such as blogs, online shopping sites, and consumer review
20 sites. Due to the information shared with a wide and geographically dispersed group of people, readers' concern about the credibility of the reviews is potentially increased (C. M. K. Cheung & Thadani, 2012). Thus, many recent literatures were investigated platform’s credibility which is defined as the degree to which readers perceive the source is trustworthy and objective in sharing the information (C. M. K. Cheung & Thadani, 2012; Z. Liu & Park, 2015).
In line with that concern, platform credibility has shown a positive influence on information usefulness because it reduces the customer’s uncertainty regarding service quality and performance during decision making process (Z. Liu & Park, 2015). This is also proves that the credibility of information vehicle can gain the consequences of eWOM as it increases consumer’s confidence about the online reviews (C. Park & Lee, 2009). In other words, the eWOM effect is greater for websites with established reputation compare with the one with less credible reputation.
Furthermore, according to Elaboration Likelihood Model (ELM), source credibility tends to function as a peripheral cue which people use to assess the reviews content itself (C. M. K. Cheung & Thadani, 2012; Sussman & Siegal, 2003). As a peripheral cue, it changes the reader’s evaluation more significantly for those who are less-involved with the topic rather than those who highly involved. Accordingly, it seems that the combination of messenger and message characteristics significantly influence how consumer perceived the usefulness of reviews. However, some earlier studies, failed to explain a strong effect of source credibility on information adoption
21 because there are some additional cues which also contributed to the peripheral process (Sussman & Siegal, 2003).
2.5 Message Contents
As explain in the previous section, the key factors of online reviews such as valence, reviews volume, and source credibility are able to influence the degree to which message receiver cognitively elaborates a certain message. This elaboration involves considering and scrutinizing the content of the message as well as assessing its relevancy. In regards to this cognitive effort, there are two different types of message content underlying the elaborations which are, informative content and emotional content (Sussman & Siegal, 2003; Yin, Bond, & Zhang, 2014; Yoo & MacInnis, 2005). An informative message is designed to attract reader’s rationality about the content and taking them to focus on the quality of the message prior to forming a judgment toward particular information (Bhattacherjee & Sanford, 2006; Yoo & MacInnis, 2005; Z. Zhang et al., 2010). Meanwhile, reader’s attitudes toward information brought about by emotional messages that are mainly driven through feelings and emotions (Yin et al., 2014; Yoo & MacInnis, 2005). Based on Yin et al. (2014), most of message recipients unconsciously process emotional cues faster and more efficient compared to informative cues. Thereby, some scholars argue that emotional content is more crucial in effecting perceived usefulness of the reviews (Yin et al., 2014).
The important role of affect and emotion cues has expanded dramatically into eWOM studies, prior to the usefulness of the information which explain consumer’s intention to adopt the message (C. M. K. Cheung & Thadani, 2012; Z. Liu & Park, 2015; Mudambi & Schuff, 2010; Yin et al., 2014). According to Davis (1989), perceived usefulness refers to “the degree to which a person believed that using a particular system would
22 enhance his or her job performance” (p.320). This indicates the online platform that offer useful reviews will help consumers decrease their perceived risk in order to increase confidence in the purchase decision (Z. Liu & Park, 2015). In the relation to consumer behavior, it appears to be the most crucial factor in predicting behavioral intention when evaluating the messages, especially if they have an association to current and future perceptions (J. Zhang & Mao, 2008).
In regard to the online reviews in travel industry, information usefulness definition aim to predict intended use (J. Zhang & Mao, 2008), but more concern about certain benefit that readers perceived from specific online network. Online network, such travel communities, offer variety of knowledge-sharing among fellow travelers that perceived as useful messages in their decision making process (Casaló et al., 2011). Since it is believed as a key construct of information adoption, some determinants that generate information’s usefulness of online review have been discussed both from the message factors and source factors (Casaló et al., 2011; Z. Liu & Park, 2015; Sussman & Siegal, 2003).
2.6 Information Adoption
Within customer’s information process, the possibility of information adoption will increase when customers regard the information useful for their purposes. This fact is supported by the model that was mostly applied in explanatory researches such as e-commerce in financial service, intention to follow the online recommendation, and purchase decision (Casaló et al., 2011; C. M. K. Cheung & Thadani, 2012; McKechnie, Winklhofer, & Ennew, 2006). A research by Casaló et al. (2011), adapt this model to explain the intention to follow online review by focusing on the cognitive components such as trust on online source and perceived usefulness of the messages. While some studies also applying the Technology Acceptance Model by Davis (1989) to explain the formation of
23 information adoption by using the same antecedence factors (Casaló et al., 2011; C. M. K. Cheung & Thadani, 2012; Jalilvand et al., 2011; Sussman & Siegal, 2003). Drawing upon the model, many evidences have established the direct relationship between online reviews as usefulness of eWOM and information adoption process by involving both central influence and peripheral cue (Sussman & Siegal, 2003).
According to other model called ‘social communication model’, this adoption will perform as a response of communication process which believed affected by message elements and message source which in this process act as stimuli and communicator (C. M. K. Cheung & Thadani, 2012). However, in one extent the magnitude of this relationship is also depending on some external factors which perform as moderators. This variation of eWOM’s effect might be caused by different characteristics of the readers and their behavior in processing information (Zou, Yu, & Hao, 2011). Regarding to that fact, many studies proved both demographic and psychographic play important role in determining the behavioral intention which effect central and peripheral routes on consumer purchase decisions (C. M. K. Cheung & Thadani, 2012).
2.7 External Factors: Demographic Characteristics
Consumers’ gender is one of demographic characteristics that proved to have significant impact on search behavior and information processing in the online environment (Gretzel & Yoo, 2008; E. E. K. Kim, Mattila, & Baloglu, 2011). Women are consider as more detail in processing message, while men tend to consider small amount of cues for their decision making process (E. E. K. Kim et al., 2011). Furthermore, Ling & Yazdanifard (2014) reveal that females are more likely to purchase experience product with hedonic motivation, while male more interesting in search product with utilitarian searching
24 behavior. Even though this is clearly indicates that women might be more heavily influenced by WOM as they are more willing to accept advices than men (Ling & Yazdanifard, 2014), a contradict findings acknowledge if women are less attracted by online searching activities than men (Hasan, 2010).
In regard to age, differences in consumer behavior also occur between different groups (Patterson, 2007). Generally, online conversations are more likely to happen for younger groups because they are more familiar with new communication technologies compared to older adults (Chung, Park, Wang, Fulk, & McLaughlin, 2010; Gretzel & Yoo, 2008). Older groups perceive learning new online technology are more difficult and give them a high level of discomfort compare with younger groups (Morris, Venkatesh, & Ackerman, 2005; Saunders, 2004). In the tourism sector, although previous studies suggest that older group are influenced by the traditional WOM recommendation (Patterson, 2007), electronic WOM has different result since they perceive such information as not up-to-date. However, several findings show that there are no difference ages in perceived difficulty for online community participation. Thus, prior researches fail to convince the moderating effect of age in the effect of online word of mouth to consumer behavior (Chung et al., 2010).
2.8 External Factors: Psychographic Characteristics
This research included psychographic characteristics which are consumer-expertise, impulsiveness and time pressure into information adoption process. Consumer expertise refers to consumer prior knowledge for a certain product or buying experience that influencing their perception toward new information and has an important role in their information searching process (C. Cheung et al., 2012; C. M. K. Cheung & Thadani, 2012; E.
25 E. K. Kim et al., 2011). In this matter, the level of consumer expertise can be measured through three aspects; objective knowledge, subjective knowledge, and product familiarity. Objective knowledge refers to consumers’ actual knowledge about a product or service, while subjective knowledge indicates consumers’ perceived knowledge that they have about certain (Hao, Ye, Li, & Cheng, 2010). However, most of prior literatures regarding consumer expertise only focus on subjective knowledge as it is believed to have greater impact on consumer’s information seeking process (C. Cheung et al., 2012; Hao et al., 2010; D. Park & Kim, 2009).
Another characteristic is consumer’s impulsiveness which is known as the extent to which people making unintended, immediate, and unreflective purchase that have been associated with self-regulatory failure in shopping context (Floh & Madlberger, 2013; Sharma, Sivakumaran, & Marshall, 2014). Consumer with high level of impulsiveness will be more emotionally attracted to products and thus the affective components overcome the cognitive (Floh & Madlberger, 2013). Further, three different dimensions have been identified regarding consumer impulsiveness (Sharma et al., 2014);
1. Self-indulgence: lies in affective dimension where consumers are tend to spend money to buy things for their pleasure and enjoying life (hedonism)
2. Lack of self-control: lies in the behavioral dimension where consumer unable to control their emotion regulation and maintain self-discipline, or quit from bad habits.
3. Imprudence: it is a cognitive dimension that consumers tend to think unclearly and unable to plan something beforehand or solve complex problems.
26 Since impulse buying most affected by shopping environment, online reviews from the website or online community play an important role in affecting consumer impulsiveness (Verhagen & van Dolen, 2011).
Finally, time pressure perceived and considered as situational factor influencing consumers’ decision within buying process that identifies time and emotion as the key drivers (Y. Lin & Chen, 2013). A research found that the level of time pressure and impulse buying significantly moderates the effect of shopping motivation on consumers’ behavior that establish both factors as relevant constructs for understanding shopping behavior (H. Kim & Kim, 2008; Y. Lin & Chen, 2013). However, some literatures see time pressure in different perspective. Online consumer perceived time pressure as their tool to save time strategy rather than constraint, especially to reduce their activity level (Richbell & Kite, 2007).
2.9 Factors Affecting The Online Travel Behavior
In the studies about electronic word-of-mouth (eWOM), there are many factors that are influencing the customer online behavior. For example, Ivan Wen (2009) reveal the impact of trust (Casaló et al., 2011; Soliman, Connolly, & Bannister, 2008; Sparks & Browning, 2011) and satisfaction (Law & Bai, 2008; SanJosé-Cabezudo, Gutiérrez-Arranz, & Gutiérrez-Cillán, 2009) to consumer purchase decision. Moreover, some literatures also mention other factors such as, brand equity dilution effect (Bambauer-Sachse & Mangold, 2011; Huang, Schrank, & Dubinsky, 2004) and price perception (Chen, Fay, & Wang, 2011; Degeratu, Rangaswamy, & Wu, 2000; Jiang & Rosenbloom, 2005). Although, researcher aware of these factors, current research only focus on level of message positivity and reviews volume as information stimuli, and platform credibility as source which summarized
27 in table 2. Consumer characteristics both demographic and psychographic also taken into account as moderator effects.
Table 2 Key Elements Associated with Information Process in Online Context
eWOM Elements Definitions Prior Studies
Stimuli
Message Positivity
Level
Reviews Volume
The message transmitted by the communicators
Direction of reviews and recommendations
Total number of posted reviews
Cheung & Thadani (2012) Gershoff et al. (2003),Chevalier (2006), Lee et al. (2008), Forman et al. (2008) Vermeulen & Seegers (2009), Mudambi & Schuff (2010), Zhang et al. (2010), Schlosser (2011)
Duan et al.(2008), Zhang et al.(2010), Lin et al.(2011), Berger et al. (2010), Davis & Khazanchi (2008), Zhang et al.(2014) Source (Communicators)
Platform credibility
Entity who transmits the communication
Platform’s perceived ability and trustworthiness to transmitting the message
Cheung & Thadani (2012)
Park & Lee(2009), Lu et al (2010), Wu et al (2010), Dou et al 2012), Sussman & Siegal (2003), Zhang et al. (2014)
Response
Information
Adoption
Main effect from the message transmission
A process in which people purposefully manage in using transmitted information
Cheung & Thadani (2012) Caselo (2011), Jalilvand (2011), Sussman & Siegal (2003), Zhang et al.(2014)
Receiver’s Characteristics
Demographics
Psychographics
Individual that responds to the communication
Gender (female/male) and age
Expertise, impulsiveness, and time pressure
Cheung & Thadani (2012)
Gretzel & Hyan-Yoo(2008), Kim et al.(2011), Ling & Yazdanifard (2014), Petterson (2007), Chung et al. (2010)
Kim et al.(2011), Cheung et al.(2012), Zou et al.(2011), Floh & Madlberger (2013), Sharma et al.(2014), Verhagen & Van Dolen (2011), Lin & Chen (2013), Kim & Kim (2008), Richbell & Kite (2007)
28
2.9.1 Online Travel Community
The growing number of reviews and recommendations are able to help people evaluate and make their purchase decision (Casaló et al., 2011; Z. Zhang et al., 2010). Not only for search product, online reviews of experience products related to tourism and hospitality services also provided by many platforms (Z. Liu & Park, 2015; Z. Zhang et al., 2010). According to Cheung and Thadani (2012), there are some types of eWOM;
Online discussion forums (e.g. zapak.com)
Online brand sites or shopping sites (e.g. Amazon, Booking.com, Airbnb, Travelocity)
Online consumer review sites (e.g. Epinions.com, shopping.com, TripAdvisor, Yelp)
Blogs (e.g. Xanga.com, blogger.com)
Social networking sites (e.g. facebook.com, MySpace.com, Twitter, Instagram)
In the travel industry, the majority of eWOM are in the form of shopping sites and consumer review sites. This makes the peers-generated information in this sector becomes more important for travel service providers (Simonson & Rosen, 2014). However, even both types of eWOM provide reviews and recommendation there is a slightly different characteristic between shopping sites and consumer review sites.
Shopping sites or booking sites in the travel industry, like Booking.com and Travelocity attracts customers from both the leisure and business sectors worldwide. They make an agreement with business sectors in terms of price and commission, and then offer the best price to the customers. This kind of platform also givescustomers the opportunity to write their reviews include numerical star ratings and open-ended comments about the services, and then let other customers read the reviews (Booking.com, 2015). While, consumer review sites such as TripAdvisor and Yelp provide advices from high number of customers with a wide variety of choices and planning
29 features with seamless links to booking website. In this platform, customers can also post their comments and reviews about their experiences (TripAdvisor LLC, 2015).
Additionally, since the number of people that taking part of these online communities increases every year (Casaló et al., 2011), including travelers and regular customers (Vermeulen & Seegers, 2009), peripheral cues becomes more importance both in shopping sites and consumer review sites (Mudambi & Schuff, 2010; Sussman & Siegal, 2003). That is why both massage elements and source’s credibility should be taken into account in the context of online communication process.
2.10 Literature Gap
According to literatures that have been collected, it has proven that online reviews significantly impact consumer intention to adopt information through information usefulness that they obtained from online society. Despite of the fact that, many scholars have been investigated message direction, review volume and source credibility as the antecedences of this relationship, there is still limited studies that examined the effect of messages positivity level. Besides, the determination of which factors that more influential still remain unclear. Moreover, receivers’ characteristics such as customers’ demographic and psychographic characteristics only received limited attention in online context. Therefore, In order to fill the literature gaps, this research aim to address following questions:
“Which factors of online reviews that is more influential to consumer’s intention to adopt the advices from online travel community?”
and
“Does the effect of online reviews on information adoption moderated by customer’s characteristics?”
30
2.11 Theoretical Contribution
With the objective to close the literature gap, this research would significantly contribute to research development in the context of online communication, especially in what extent customers willing to adopt the customer-generated online reviews for their purchase decision making. Furthermore, this research provides an empirical framework concerning four different components in online information process; (1) an investigation on factors that related to the information stimuli which are message positivity and reviews volume, (2) platform’s credibility that implies to communicators, (3) response that represented by the intention to adopt information, (4) receiver that examine the role of customers’ demographic and psychographic characteristics in this model.
2.12 Managerial Contribution
Some of the service providers have already proved that by adapting research findings they are able to increase their business growth up to 26% (Freedman, 2008). In Managerial perspective, online reviews give an intrinsic low maintenance tool for the travel providers, this study provides useful insights in order to effectively improve this tool as well as upgrade the quality of the products. This study also provides an observation on what factors that indeed driving customers’ buying behavior for travel online services. The results could direct marketers in travel industries to efficiently adjust their strategies in accordance to market situation. Furthermore, if marketers could identify what elements on reviews webpage which are most influential to information adoption, they could develop the reviews as part of the service experience. Service product reviews give a strong revisit opportunity since lots of people could back to read the reviews anytime. Therefore, by examining the communication components, it gives recommendation to where marketing expenditure could effectively invest.
31
CHAPTER 3
CONCEPTUAL FRAMEWORK AND HYPOTHESES 3.1 Research Framework
Figure 3 Conceptual framework by the author
Underlying the design of this research, a conceptual framework has been developed in accordance with the social information process (source, stimulus, response, readers) by including four key components as depicted in Figure 3, while also describes the relationship among them. This research measures the effect of stimuli which constructed by message positivity level and reviews volume; and the source that represented by the website’s credibility as independent variables. Then, the effected variable was customers’ intention to adopt the information.
In order to address the first research question, a simple experimental design will be applied by manipulating the variables into different scenarios in data collection process. Furthermore, customer’s demographic and psychographic characteristics will be included in the data analysis to test the moderating effect from both variables on the main
H1b
H2 H1a Online Review Elements
H4b H4a, H4c H3b H3a Reviews Volume Message Positivity Demographic Gender Age differences Psychographic Consumers’ Expertise Impulsiveness Time pressure Website’s credibility Intention to adopt information
32 relationships. Accordingly, based on the conceptual framework this section will discuss further about the relationship between those components and formulate hypotheses in order to address research questions.
3.2 The Influence of Message Elements on Intention to Adopt Information
The online review elements have received a lot of attention since they demonstrate the most important factors in determining the effect of eWOM on behavioral intention (C. M. K. Cheung & Thadani, 2012; A. Davis & Khazanchi, 2008). Many researches have proved the effect of message direction in generating intention to adopt (Duan et al., 2008; Z. Liu & Park, 2015; Vermeulen & Seegers, 2009; Z. Zhang et al., 2010). In terms of usefulness of the reviews, the extremely positive cues are perceived as more useful than the moderately positive cues (Gershoff et al., 2003; Schlosser, 2011). However, there are still limited findings regarding the extremity effects of the information adoption in travel industry sectors which believed to be useful to understand travelers’ behavior.
Meanwhile, numbers of scholars convince that consumer’s purchase decisions are more effected by the number of reviews rather than its direction (D. Park & Lee, 2008). This is due to the number of reviews considered as more associated with message evaluation and could generate awareness as well as perceived quality of the reviews (Berger et al., 2010; C. Lin, Lee, & Horng, 2011a; Vermeulen & Seegers, 2009; Z. Zhang et al., 2010). Since, both elements are expected to have contributions in predicting consumer intention to adopt the information this research will investigate which element that has greater contribution. The hypotheses are formulated as follow:
H1a: Number of reviews for a travel product has greater effect on consumer intention to adopt the information than review’s positivity.
33 H1b: Highly positive reviews have greater impact on consumer intention to adopt the
information than the moderately positive reviews.
3.3 The Influence of Website’s credibility as Source on Intention to Adopt Information
In terms of the communicators, customer-generated reviews are seen as more relevant and credible source of information rather than marketer-generated one (Casaló et al., 2011; C. M. K. Cheung & Thadani, 2012; C. Park & Lee, 2009). Thereby in the context of service sectors, online community plays an important role in influencing other customers’ behavior since they can read information from fellow customers regarding particular service (Casaló et al., 2011; Li, Huang, Tan, & Wei, 2013; Z. Zhang et al., 2010). A research by Park and Lee (2009) also found that established websites have greater impact on eWOM adoption rather than non-established one due to it is indicating the quality of the message. Due to the online-community websites act as the source of information, there is a notion this source is the key factor that effecting consumer behavior in an online environment. Thus, purposed hypothesis is:
H2: The credibility of online-community website is more influential to customer intention to adopt the information than the reviews’ positivity and messages volume.
3.4 Moderating Effects of Customers’ Demographic Characteristics
In the online environment, men and women have different ways to process information as numbers of study find that men are more focus on useful information than women (E. E. K. Kim et al., 2011). Due to women, in consequence, are more detail and processing all information available in effortful way, they are easier to be influenced by the eWOM rather than men (E. E. K. Kim et al., 2011; Ling & Yazdanifard, 2014). Thus, gender
34 differences are expected to have moderating effect on the effect of message elements to intention to adopt the review that that leads to hypothesis:
H3a: The effect of reviews’ positivity, message volume and the credibility of online community website will be greater in women compare to men.
In terms of age, research by Patterson (2007) reveal that traditional WOM is one of the most powerful sources which used by older customers during the decision making process, especially in travel sectors. However, in the context of eWOM, numerous literatures reveal that young and well educated customers are customer who more likely use travel community websites for their destination planning (Gretzel & Yoo, 2008; Ip & Law, 2010). This is because older groups perceive online platform as complex and difficult to learned (Alreck et al., 2011). Hence, following hypothesis is purposed:
H3b: The effect website’s credibility on customer intention to adopt the information will be greater for younger groups of customers than older groups.
3.5 Moderating Effects of Customers’ Psychographic Characteristics
Several works have noted the moderating effects from customers’ characteristics on their intention to adopt information from online reviews. In this research three different characteristics will be examined. First, the interaction effect customer’s expertise will be evaluated in this study. Consumer expertise defined as subjective knowledge or consumers’ perceived knowledge about certain product or service since it influences consumers’ information search and processing behaviors more directly than objective knowledge (C. Cheung et al., 2012; C. M. K. Cheung & Thadani, 2012; Hao et al., 2010). In the online environment, consumer who has a high level of perceived knowledge towards online travel communities will be less sensitive to information because they are more confident in
35 decisions making which reduces the effect of message positivity on information adoption (C. Cheung et al., 2012; D. Park & Kim, 2009). Therefore, the hypothesis will be formulated as follow:
H4a: The impact of review positivity on intention to adopt information is stronger for low-expertise customers than for high-low-expertise customers.
Second, as research by (Y. Lin & Chen, 2013) highlighted that consumer behavior toward dining and recreational commercial may change with an intervened from the degree of impulsive trait, level of customer impulsiveness will be evaluated. This consumer trait evidently has been greater for internet shopper than in-store shopper (Kaisheng, 2010b), which is strongly related to their buying behavior (Floh & Madlberger, 2013; K. Z. Zhang et al., 2014). However, little is known about consumer-generated stimuli regarding this context. Since (Y. Liu, Li, & Hu, 2013) found that consumer impulsiveness in online social interaction is triggered by the website characteristics, this traits are expected to moderate the relationship between platform’s credibility and information adoption behavior. Therefore following hypothesis is proposed:
H4b: The impact of website’s credibility on intention to adopt the information is stronger for customers with high-level of impulsiveness than the one with low-level of impulsiveness.
Finally, this research consider the time pressure as time constraint for customer during their buying decision process. The level of time pressure expected to influence the relation between message volume and intention to adopt the information as some research demonstrates its moderating effect in information processing system (Alreck et al., 2011; Y. Lin & Chen, 2013; Reutskaja, Nagel, Camerer, & Rangel, 2011). In light of Elaborate
36 Likelihood Model (ELM), customers with time constrain are low motivated customer who tend to make suboptimal decision based on peripheral cue such as number of argumentations which in this case are peer-reviews volume (C. Lin, Lee, & Horng, 2011b). Thereby, the time pressure is anticipated to moderate the effect of review volume as purpose in following hypothesis:
H4c: The impact of number of reviews for a service product on intention to adopt information will be greater for customer with higher time pressure compared with customer with lower time pressure.
37
CHAPTER 4
RESEARCH DESIGN AND METHODOLOGY 4.1 Research Design
A deductive approach is applied to explain the causal relationship between variables by using explanatory study in the cross-sectional research process. As mentioned the independent variables in this study were message positivity and reviews volume as constructs of review elements; and website’s credibility. While, the dependent variable was customer intention to adopt information from travels online communities. This study also analyzed the moderator factors on the relationships between independent and dependent variables by involving customer’s age and gender as demographic characteristics; and customer’s expertise, impulsiveness, time pressure as psychographic characteristics.
In order to test the hypotheses, a combination of online survey and a simple experimental design was engaged using 2 x 2 x 2 as factorial design. This combination employed not only because the object is online behavior, but also because the high possibility to reach diverse demographic population, in efficient time and money, as well as to keep the convenience of the respondents in answering the questionnaires (Reips, 2000). Moreover, this research is assessing the variation of impact from every single independent variable while systematically controlling other independent variables. In other words, scenarios with different control variables will be given to different respondents that assigned randomly through online survey. These scenarios were adapted in correspond to the intention of this study using Adobe Photoshop CS3.
4.1.1 Treatment Object
Since this study focus on information adoption within online travel community, the treatment object that was employed is hotel booking website which contain
38 customer-generated online reviews. Moreover, customer intention to adopt the message is easier to measure in booking website rather than customer online review sites. The treatment was developed in different scenarios or conditions in order to measure the effect of tested variable. Then, researcher measured the response of controlled variables that were adjusted in the hotel booking webpage through item measurements during the experiment. Real hotel booking websites were used for the treatment without changing the layout and style to ensure the respondents valuation of ‘website credibility’ variable. However, the captured webpage contained fictitious hotel name and picture to avoid bias due to customer’s prior knowledge about the hotel. Since the samples were International respondents in Netherlands, a tropical trip destination was chosen with expectation that the sample respondents have limited relevant information about the location and tends to fully rely on the information provided on the webpage.
4.2 Experimental Design
The online experiment conducted with a 2 (level of positivity) x 2 (reviews volume) x 2 (platform’s credibility) factorial design by manipulating different controlled variables into eight different conditions. As illustrated in Figure 4, four conditions are from Booking.com as high reputable website according to (Top Ten Reviews, 2015) and four others from ratestogo.com which consider as less reputable website (ProductReview.com, 2015).
39 The detailed description will be explained as follow. Condition 1 showed message with high positivity from Booking.com with 9.0 rating out of 10 from 500 reviewers. Whereas, low level of positivity messages with 7.5 out of 10 as a rating displayed in condition 2 while other elements stay the same. The other conditions show screen capture from Ratestogo.com as low reputable website. For condition 5, 500 reviewers are indicated along with positively framed messages rated by 9.0 and low level of positivity messages rated by 7.5 for condition 6. Finally, condition 7 and 8 were showing that only 10 people who posted reviews in that particular page for both high positivity (9.0 numerical rating) and low positivity (7.5 numerical rating) message for each condition.
4.2.1 Pilot Test and Questionnaire Structure
Before conducting the actual experiment, a pretest (pilot experiment) was managed to few respondents in order to adjusting the manipulated variables if needed. Pilot experiment refers to small versions of a full-scale study to check the feasibility of the methods or instruments. This study is conducted in order to developing the adequacy of research instruments as well as to identify possible problems that might occur (van Teijlingen & Hundley, 2001). In current study pilot test is conducted by administering the questionnaire to 2-3 respondents for each condition offline and record the time taken to complete all the questions. After they finished with the questionnaire I ask them for feedbacks to identify ambiguities and difficult questions. With all information gathered from the pretest, questionnaire was revised by discarding unnecessary and difficult questions.
After pilot test, actual data was collected by distributing eight different self-administered questionnaires through online survey (Qualtrics) with one condition in each questionnaire. The questionnaire divided into four sections of structured questions which
40 adjusted to the experimental purposes (Appendix 6). Before respondents start completing the experiment questions, they were asked whether they are familiar with hotel booking websites and whether they are actively using them for information seeking and minimize subject bias. If the respondents meet the sample requirement, they were start to completing the experiment questions.
In the first section, they were asked to indicating few questions regarding their psychographic characteristics which are expertise, impulsiveness and time pressure. In the next section a screen captured of hotel booking webpage which consist of review components was displayed along with the explanation of the manipulated situation. Afterwards, respondents were asked to indicate their judgment regarding the information provided on the image in order to make sure that respondents perceived the manipulation correspond to the research purposes. In the third section, some questions regarding their attitudes and responses toward the treatment were asked. These all questions use six-point Likert scale which allow respondents rated from 1 (“Strongly Disagree”) to 6 (“Strongly Agree”). Finally, multiple-choice questions were used to identify respondents’ demographic characteristics such as age, gender, and education level.
4.2.2 Variable Measurements
Before testing the hypothesis, prelimenary test was conducted in order to check the error and make sure if item scales were reliable. These analyses allow me to examine the consistency of items in presenting the findings and ensure if they are able to measure what this research intend to measure.
For measuring psychographic characteristics, three items were used to identify subjects’ expertise (Bearden & Netemeyer, 1999; Hao et al., 2010) which are “I have rich
41 experiences on hotel booking online”, “my knowledge help me understand very technical information about hotel reviews”, “I use my knowledge to verify if the new information I obtain are true”. For measuring subjects’ impulsiveness, three items were used (Bearden & Netemeyer, 1999; Y. Liu et al., 2013) i.e.” I often buy things spontaneously”, “I carefully plan most of my purchases”, “I often buy things intuitively rather than deliberately”. And then, to check level of time pressure two items (Y. Lin & Chen, 2013) “I do not have enough time finding information for planning my vacation” and “I must hurry if I am to complete my vacation plans in a week” were applied.
To assess the efficacy of manipulated variables some items were designed. In this study, the level of message positivity refer to the extremity of positive information provided by the review webpage which able to influence reader’s evaluation (Gershoff et al., 2003; Schlosser, 2011) about reviewed Hotel through overall ratings and one-sided messages. By using 6 likert-scale, the items “the overall valuation toward the hotel is completely positive” and “the evaluations about the hotel are very favorable” are used to measure the level of message positivity (Hao et al., 2010; Khare, Labrecque, & Asare, 2011):
Reviews volume refer to the total number of people who posted reviews for particular hotel in website page (C. M. K. Cheung & Thadani, 2012). The number that applied in the manipulated condition were based on the average postings on individual reviewed hotel. To measure the efficacy of that number, following items that were adapted from Zhang et al. (2010) and measured by using the same scale ranging (1 = “Strongly Disagree” and 6 = “Strongly Agree”):
The number of people who reviews this hotel is large (vs. small)
42 website’s credibility refer to how customers perceive the platform’s ability or competency to perform useful and truthful information (C. M. K. Cheung & Thadani, 2012). To assess this controlled variable, items which adopted from (Lu, Zhao, & Wang, 2010; J. Wu, Chen, & Chung, 2010) measured using 6 likert-scale:
I believe that Booking.com (vs. Ratestogo.com) has the ability to provide information that I need
Booking.com (vs. Ratestogo.com) appears to be well qualified in the area of hotel booking website
Furthermore, under these experiment conditions respondents intention to adopt the manipulated information was expected to be the the response. According to some prior research (Casaló et al., 2011; C. M. K. Cheung & Thadani, 2012; Z. Liu & Park, 2015) this behavior is a form of consequences of information usefulness. Therefore an items was measured whether the treatment condition helpful for respondent’s decision making or not (Wang & Chang, 2013). Then, the intention to adopt information was examined through following item scales which adapted from (Casaló et al., 2011; D. Park & Kim, 2009; Xia & Bechwati, 2008):
The reviews helped me evaluate the hotel quality
I would not hesitate to take into account comments from the webpage
I would feel secure following the suggestions from above webpage
I would rely on the recommendations on above webpage
If I have to decide now, I probably will book this hotel
I am willing to book this hotel
