Online reviews : what makes them more influential on consumers’ buying decisions

University of Amsterdam Faculty of Economics and Business

Master Thesis MSc Business Administration - Marketing Track

Online reviews: What makes them more influential on consumers’ buying

decisions.

Note

In writing this thesis, I decided to adopt the "we" form. Though, it is important to note that I am the sole author of this report and that this research is exclusively conducted by me.

Statement of Originality

This document is written by Student Keilani Gonzalez 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.

ACKNOWLEDGEMENT

I have reached the final step in attaining my Master’s degree in Business Administration at the University of Amsterdam, with the completion of this thesis. This was my first time writing a thesis of this nature and it has been an interesting learning experience. I directly knew from the first moment of choosing a subject that online reviews was a subject that I wanted to study and I am now even more interested in this field.

I would firstly like to take this opportunity to thank my supervisor Mr. Dr. Umut Konuş for all of his support and guidance during the process of writing my thesis. His constant positive criticism helped me significantly through the whole process. Furthermore, I would like to thank my family and friends who have been there for me since the beginning and who have never given up their faith in me.

I truly hope you enjoy reading this thesis and that it spikes an interest in this topic area.

Kind regards,

Keilani Gonzalez

ABSTRACT

The Internet has caused a shift to occur with regard to word-of-mouth (WOM). WOM has transformed into Electronic word-of-mouth (eWOM) (Hennig-Thurau, Gwinner, Walsh, & Gremler, 2004). Instead of consumers having conversations face to face, conversations are now through the Internet. There are several forms of eWOM (Cheung & Thadani, 2012) of which online reviews have been found to be one of the most important forms (Jiménez & Mendoza, 2013) and it has an effect on consumers’ purchase decision (Zhang, Cheung, & Lee, 2014). However, it is important to note that online reviews are made up of different characteristics such as; the number of reviews, valence of reviews, and source credibility, but there is still little knowledge about the effect of those characteristics on consumer’s buying intention. Even more so little is known about how the effect of those characteristics on consumers’ buying intention will differ for consumer gender and impulsiveness. Therefore, this current study researched which factors related to online reviews are more influential on consumers’ buying intention and what the demographic and psychographic factors affect are on those relations. Using an experimental survey data from 313 (mostly) Dutch consumers, it was found that the factors Number of reviews and Valence of reviews both have an effect on Buying intention and Valence of reviews is the most influential factor on consumers’ buying intention. Furthermore, it was identified that positive reviews have a greater effect on buying intention than negative reviews. Moreover, the reviewer of an online review is perceived as more credible based on their percentage of helpfulness, rather than their ranking. In addition the demographic characteristic, gender, was identified as a moderator on the relation between valence of reviews and buying intention. For female consumers’ as the review becomes positive there is a strong increase in their buying intention. For male consumers there is also an increase in buying intention, however it is less. This study concludes with managerial implications of the results and suggestions for future research.

TABLE OF CONTENTS

1. INTRODUCTION ... 9

2. LITERATURE REVIEW ... 14

2.1. Word-of-mouth (WOM) ... 14

2.2. Electronic word-of-mouth (eWOM) ... 15

2.3. Consumers’ buying intention ... 17

2.4. Online reviews ... 17

2.4.1. Online reviews on consumers’ buying intention ... 18

2.4.2. Characteristics of online reviews ... 20

2.4.2.1. Scope of this study ... 20

2.4.2.2. Number of reviews ... 21

2.4.2.3. Valence of reviews (Positive vs. negative reviews) ... 22

2.4.2.4. Source (reviewer) credibility ... 25

2.5. Consumers’ demographics and lifestyle ... 25

2.5.1. Consumers’ gender ... 26

2.5.1.1. Moderating effect of consumer’ gender ... 26

2.5.2. Consumers’ impulsiveness ... 27

2.5.2.1. Moderating effect of consumers’ impulsiveness ... 27

2.6. Literature Gaps and Research question ... 31

2.7. Theoretical and managerial contribution ... 32

3. CONCEPTUAL FRAMEWORK ... 34

3.1. Hypotheses ... 35

4. RESEARCH DESIGN AND METHODOLOGY ... 40

4.2. Research design ... 41

4.2.1. Experimental survey and procedure ... 42

4.2.2. Measures ... 44

4.3. Procedure data collection ... 46

4.3.1. Pilot studies ... 46

4.3.2. Main study ... 47

5. RESULTS AND ANALYSIS ... 49

5.1. Preliminary Analysis ... 49

5.2. Reliability and scale means ... 49

5.3. Descriptives and Comparisons ... 50

5.4. Analysis Results ... 51

6. DISCUSSION AND CONCLUSION ... 56

7. MANAGERIAL IMPLICATIONS ... 63

8. LIMITATIONS AND FUTURE RESEARCH ... 66

9. REFERENCES ... 68

10. APPENDICES ... 77

I. The Treatments ... 77

II. The Experimental Survey ... 79

III. Dummy Variables ... 83

TABLE OF FIGURES AND TABLES

Figure 1. Example of an online review ... 17

Figure 2. Purchase influence of online reviews (in the US) (MarketingCharts, 2012) ... 19

Figure 3. Conceptual framework ... 34

Figure 4. Effect of valence of reviews on buying intention of male and female consumers ... 54

Table 1. Online review characteristics that will be studied and their definition ... 21

Table 2. Review of online reviews' characteristics on consumers' buying intention literature and effect of gender and impulsiveness ... 29

Table 3. Gaps in the current literature ... 31

Table 4. Hypotheses ... 39

Table 5. 2 x 2 x 2 Factorial Design ... 42

Table 6. ANOVA: Test between Subjects effects - Main effects and Interaction effects ... 55

1. INTRODUCTION

The Internet has really grown in the past twenty years (Cheung, Lee, & Rabjohn, 2008). This technology development has caused a shift to occur with regard to word-of-mouth (WOM), which is the face-to-face interaction or conversation between people. The shift that has occurred as stated by Hennig-Thurau, Gwinner, Walsh, and Gremler (2004) is that WOM has transformed into Electronic word-of-mouth (eWOM). Instead of consumers having conversations face to face, they now have conversations through the Internet. Through this eWOM, consumers communicate to other consumers via different channels such as social media, discussion forums, and online reviews, to express their opinion and at the same time evaluate brands and/or products (Hennig-Thurau et al., 2004). There are several forms of eWOM namely; online discussion forum, online review sites, blogs, social networking sites, and online shopping sites (Cheung & Thadani, 2012). However, online reviews have been found to be one of the most important forms of eWOM (Jiménez & Mendoza, 2013).

So what are online reviews specifically? Well, online consumer reviews are a specific type of eWOM that can be defined as peer-generated or consumer-created product evaluations (Jalilvand, Esfahani, & Samiei, 2011; Mudambi & Schuff, 2010). Furthermore, according to Jiménez and Mendoza (2013) online reviews can be described as having graphical and/or textual elements that allow consumers to assess and determine the usefulness of the reviews for their purchase decision.

In a 2011 consumer survey about global consumer shopping habits by Channel Advisor, they found that 90% of online shoppers read online reviews, while 83% believe that these reviews actually affect their purchase behavior (Zhang, Cheung, & Lee, 2014). Furthermore, eMarketer stated that in a 2012 survey by Ipsos OTX and Ipsos Global @dvisor, it was found that 78% of Internet users (in the US) considered ratings and online

reviews influential when making buying decisions (Zhang et al., 2014). In addition, in a 2012 survey by ReviewInc and Pepperdine University it was found that 86% of consumers that were surveyed used reviews before doing business with a company (Garcia, 2013).

As mentioned, online reviews are one the most important forms of eWOM and it is an important form of information that allows consumers to search for detailed and reliable information by sharing past consumption experiences (Liu & Park, 2015) and it affects consumers’ purchase decision (Zhang et al., 2014). In a 2007 survey by Deloitte’s Consumer Products group, it was found that 62% of consumers read online consumer reviews (MarketingCharts, 2007). Even more interesting is that of those consumers who read online reviews, 82% of them indicated that the online reviews directly influenced their purchase decisions as well as their purchase intention (MarketingCharts, 2007). Furthermore, according to the article by Garcia (2013) reviews play a large role in consumers’ purchase decisions no matter the industry. According to Gesenhues (2013) in a survey conducted by Dimensional Research, they found that 88% of the respondents stated that all online reviews (positive and negative) influenced their buying decision. In the Influence Central research (2014) it was found that only 3% of consumers consider online reviews to be very unimportant and only 1% consider them not important at all, which indicates that many of the consumers do find online reviews important when making a product purchase.

Seeing as the Internet has grown rapidly and now consumers are using the Internet more and more to communicate with other consumers, this study will focus on how factors of online reviews could affect consumers’ buying intention. Consumers’ buying intention can be seen as a measure of the possibility that a consumer will purchase/buy a product, meaning that the higher the purchase intention expressed, the greater the possibility and probability that the consumer will actually buy the product (Schiffman & Kanuk, 2000). There are

several studies that find that online reviews positively affect consumers’ buying intention (Senecal & Nantel, 2004; Godes & Mayzlin, 2004; Lin, Luarn, & Huang, 2005).

However, it is important to note that online reviews are made up of different characteristics/factors, which can also have an effect on consumers’ buying intention, which is why the main focus of this study will be on that specific effect. Some of the characteristics of online reviews are; source credibility, quality of the review, number of reviews, and valence of reviews (whether the review is positive or negative). Because of the scope and time of this study, we will not be able to test for all characteristics and therefore we will focus on the following three; number of reviews, valence of reviews, and source credibility. There are a few researches that investigated the effect of number of reviews, however only a few looked at the effect it would have on consumers’ buying intention. On the relationship between the valence of online reviews and consumers’ purchasing intention there are a few studies that show an inconsistent relationship (Zou, Yu, & Hao, 2011), some studies find that a positive review has more impact on buying intention, other studies find that it is negative reviews and not positive reviews that have a greater impact, and there are even some studies that find no significant relationship between the two variables.

Besides the characteristics of online reviews (number of reviews, valence of reviews, and source credibility), there are also other factors for which the effect of those characteristics on buying intentions might differ. Those other factors are the moderating variables gender (consumer demographics) and impulsiveness (consumers’ lifestyle).

In a research by Influence Central on E-Commerce reviews in 2014 85% of female consumers consider e-commerce reviews when making a purchase very important (Influence Central, 2014). So, it will interesting to see whether the characteristics/factors of online reviews will have a different effect on female consumers’ buying intention than on male consumers’ buying intention in this study.

Furthermore, with consumers’ lifestyle the focus will be on consumers’ impulsiveness. From the existing literature it is not completely clear what the effect is of valence of reviews on female or male consumers’ buying intention. And finally, with regard to the impulsiveness of consumers, there are only a small number of studies that look at the relationship between impulsiveness and buying intention, and even more so, non of those studies look at the effect of the number of reviews or valence of reviews on impulsive consumers’ buying intention.

This study is of practical value and relevance to firms and managers, because it is not only important for a firm and its managers to know whether certain characteristics of online reviews influence consumers’ buying intention, but more importantly which characteristics of online reviews are most influential on consumers’ buying intention. If there is an agreement about which characteristic(s) have a significant effect on consumers’ buying intentions, managers can allocate more resources on creating online reviews with those specific characteristics. They might also be able to encourage consumers to create more online reviews but focusing on specific characteristics. In addition, if firms and managers know to what extent those characteristics differ among male and female consumers, and impulsive consumers, then managers can acquire experts and set up strategies to manage these online reviews more efficiently and effectively, and so to reap of benefits of online reviews. So, by setting up strategies firms and managers can focus on resource as well as budget allocation more specifically on the characteristic(s) that are found to be the most influential, meaning firms will not need to spent more on every aspect of online reviews but only on those most significant. Furthermore, by knowing which characteristic(s) are more influential and how they differ between male and female consumers and impulsive consumers, firms and managers can focus on the content development of the online reviews. By doing this it will increase the chance of affecting the buying intention of their consumers because they are targeting those specific consumers by focusing on the specific characteristic(s).

The theoretical relevance of this study is that it adds to the literature by investigating more deeply to what extent different characteristics of online reviews influence consumers buying intention, and also whether the influence of those characteristics differ with regard to other factors (gender and impulsiveness).

In an online experimental survey, participants will get to see two online reviews about a search product namely a digital camera. Based on these online reviews the participants will be asked different questions so to be able to measure the variables and be able to test the hypotheses developed.

Thesis overview

This research is structured in the following chapters. In the next chapter a review of the literature on the key concepts about WOM, eWOM, online reviews, consumers’ buying intention, characteristics of online reviews, and consumers’ lifestyle (impulsiveness) and demographics (gender) are discussed. Furthermore, a theoretical framework about the characteristics of online reviews on consumers’ buying intentions is developed, as well as for the moderating variables gender and impulsiveness. In the third chapter the conceptual framework is presented and hypotheses are explained and formulated. In the following chapter the research design and methodology is explained. The results of the research will then be presented in chapter five. And finally, the empirical findings are discussed in the Discussion chapter and the conclusion is given. Hereafter, the managerial implications are explained and lastly the limitations and suggestions for further research are discussed.

2. LITERATURE REVIEW

This chapter provides a comprehensive review of the literature about the key concepts in this study, in order to analyze what has already been studied about characteristics of online reviews on consumers’ buying intention and also the moderating effect of consumers’ impulsiveness and gender. First, some basic information about WOM and eWOM is given. Next, previous research about the key variables; online reviews, characteristics of online reviews, and their effect in consumers’ buying intention are reviewed. Then, a detailed analysis of the possible associations with consumers’ impulsiveness and demographics is given. Finally, based on this review, a conceptual framework and hypotheses are developed and will be tested in this study.

2.1. Word-of-mouth (WOM)

To be able to explore electronic word-of-mouth (eWOM), it is important to first clarify what offline word-of-mouth (WOM) is. Traditional offline word-of-mouth (WOM) involves face-to-face two-way communication within a social relationship (Prendergast, Ko, & Yuen, 2010). In offline WOM one message can reach and potentially influence many receivers, but usually by passing through a chain or tree of correspondents (Lau & Ng, 2001).

There are many definitions and explanations for WOM, one of the earliest was by Arndt (1967) and he characterized WOM as oral, person-to-person communication between a receiver and a communicator whom the receiver perceives as non-commercial, regarding a brand, product or service. WOM has been stated to be a form of interpersonal communication among consumers concerning their personal experiences with a firm or a product and it “has undoubtedly always been a powerful marketing force” (Sundaram, Mitra, & Webster, 1998, p. 527). The reason for this is because consumers when making purchase decisions often depend on information and/or personal communication sources instead of depending on more

formal and/or organizational sources such as advertisements (Bansal & Voyer, 2000). In WOM the source or sender of the information usually has nothing to gain from the receiver’s subsequent actions following from the information they received (Bansal & Voyer, 2000).

WOM gained significance because of the persuasive role it plays in influencing consumers’ attitudes and purchase decisions (Sundaram et al., 1998). It was shown that WOM communication has an impact on purchase decisions and choice behavior of consumers (Prendergast et al., 2010). Both positive and negative WOM can have strong influence on consumers’ behavior, because it was found that positive WOM most likely increases consumers’ purchase intentions and negative WOM actually decreases consumers from buying a particular product (Sundaram et al., 1998). Additionally, offline WOM communication has an impact on consumers’ attitudes (Brucks, 1985) and purchase decisions and choice behavior (Lau & Ng, 2001). In the study by Bounie, Bourreau, Gensollen, and Waelbroeck (2005) they actually found that face-to-face WOM has a significant negative impact on purchases.

Even though WOM gained significance, there was a shift from face-to-face communication to communicating via the Internet.

2.2. Electronic word-of-mouth (eWOM)

Web 2.0 has enabled new forms of communication that further empower providers of products and services but also consumers, allowing a platform for the sharing of information and opinions both from Business to Consumer, and from Consumer to Consumer (Jalilvand et al., 2011). Consumers increasingly use the Internet to communicate with other consumers as well as to review and purchase products (Jiménez & Mendoza, 2013). Communicating via the Internet is considered to be Electronic word-of-mouth (eWOM), which 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”

(Hennig-Thurau et al., 2004, p. 39).

There are three dimensions that contribute to the uniqueness of eWOM compared to WOM. eWOM communications (Cheung & Thadani, 2012) namely;

1. Possess exceptional scalability and speed of circulation. It involves multi-way exchanges of information that is not occurring at the same time.

2. Are more persistent and accessible. The reason for this is that most of the time text-based information on the Internet are archived and consequently are available for an indefinite period of time.

3. Are more measurable than traditional WOM. They are more measurable because the presentation format, quantity, and persistence of eWOM communications have made them more observable. eWOM is far more voluminous in quantity compared to WOM in the offline world. Simply said, a large number of eWOM messages can be easily retrievable online.

Furthermore, according to Cheung and Thadani (2012) a number of studies have identified five types of eWOM in the online environment namely; online discussion forums, online consumer review sites, blogs, social networking sites, and online brand/shopping sites. In addition, Jiménez and Mendoza (2013) indicated that online reviews are one very important form of eWOM. Research reports have shown that when making purchase decisions, Internet users trust online reviews posted by unknown consumers more than they trust traditional media (Cheung & Thadani, 2012). According to the research by Prendergast, Yuen, and Tong (2009) online WOM (eWOM) has the capability to significantly influence consumer behavior. Furthermore, in the study by Bounie et al. (2005) on the effect of online consumer reviews on purchasing decisions (they looked at the case of video games), they found that online information has a significant positive effect on (video game) purchases. There are several other studies that show that eWOM influences consumers behavior, namely

the study by Chen, Wang, and Xie (2011), Hennig-Thurau et al., 2004, Jalilvand and Samiei (2012), Jiménez and Mendoza (2013), and Wang (2011).

2.3. Consumers’ buying intention

Before continuing on to the literature on online reviews and their effects on consumers’ buying intention, we find it important to first clarify what we mean with consumers’ buying intention in this study. Purchase or buying intention can be categorized as one of the elements of consumer cognitive, or rational, behavior on how an individual intends to buy a specific brand or product (Ling, Chai, & Piew, 2010). In other words, purchase or buying intention can be seen as a measure of the possibility that a consumer will purchase/buy a product, meaning that the higher the purchase intention expressed, the greater the possibility and probability that the consumer will actually buy the product (Schiffman & Kanuk, 2000). So, for this study we hold that consumers’ buying intention is the extent to which a consumer is willing to purchase a product.

2.4. Online reviews

Online reviews (Figure 1) as mentioned before are a form of eWOM and according to Jiménez and Mendoza (2013) they are a very important form of eWOM. Before we discuss why online reviews are important, we find it imperative to have a comprehensive discussion about what online reviews are.

As stated by Jiménez and Mendoza (2013) online reviews in most cases consist of graphical and/or textual elements that allow consumers to

assess and determine the usefulness of the reviews for their purchase decision. Online consumer reviews are a specific type of eWOM that can be defined as peer-generated or consumer-created product evaluations which are helpful and impact consumer buying decision process, because it provides consumers with indirect experiences (Jalilvand et al., 2011; Mudambi & Schuff, 2010).

It has been argued that the reason for the increase of importance of online reviews is because it allows consumers to search for detailed and reliable information by sharing past consumption experiences (Liu & Park, 2015). As mentioned with regard to WOM, when consumers make purchasing decisions they rely on information and/or personal communication sources rather then on more formal and/or organizational sources (Bansal & Voyer, 2000), for online reviews the same can be said. Research reports have shown that when making purchase decisions, Internet users trust online reviews posted by unknown consumers more than they trust traditional media (Cheung & Thadani, 2012).!

2.4.1. Online reviews on consumers’ buying intention

Online reviews can function as informants and as recommenders, and these functions are important in making purchase decisions (Park, Lee, & Han, 2007). According to Zhang et al. (2014) online reviews can be an important form of information that affects consumers’ purchase decision. In a 2010 consumer shopping habits survey, user-generated content in the form of online customer reviews was found to significantly influence consumers’ purchasing decisions (Cheung & Thadani, 2012). In a 2011 consumer survey about global consumer shopping habits by Channel Advisor, they found that 90% of online shoppers read online reviews, while 83% believe that these reviews affect their purchase behavior (Zhang et al., 2014). Furthermore, eMarketer stated that in a 2012 survey by Ipsos OTX and Ipsos Global @dvisor (Figure 2), it was found that 78% of Internet users (in the US) considered ratings and online reviews influential when making buying decisions (Zhang et al., 2014).

! Figure 2. Purchase influence of online reviews (in the US) (MarketingCharts, 2012)

!

In addition to these findings, the study by Senecal & Nantel (2004) strongly supports the argument that consumers are influenced in their online product choices by online recommendations. According to the article by Godes and Mayzlin (2004), people make purchasing decisions based on consumer-created information over the Internet (and this can be seen as eWOM or more specifically online reviews). In the study by Jang, Prasad, and Ratchford (2012) they studied how consumers use product reviews in their purchase decision process, they looked at the consideration stage and choice stage of consumers. In their study it was found that when consumers are in the consideration stage (consumers select products for further evaluation), they use product reviews more than when they are in the choice stage (consumers choose the final product) (Jang et al., 2012). From this we could assume that when consumers are considering products to buy they use online reviews, but when they need to make the final choice of purchase online reviews are not used as much. However, the findings of a study indicated that more than 80% of web shoppers stated that they use consumers' reviews when making purchasing decisions (Gretzel & Yoo, 2008). In addition,

in a study they found that over 80% of purchase decisions are made on the basis of consumer word-of-mouth communications (Lin et al., 2005). Also Lin et al. (2005) found in their study about Internet book reviews, that the majority of the participants indicated that online book reviews affected their purchase intention. Lee and Kwon (2008) also showed in their study that online recommendations can lead to consumers' attitude towards a recommended product being enhanced and can positively influence consumer decision-making. The majority of the studies in the area about online reviews’ effect on consumers’ buying intention are unanimous about the fact that they most definitely influence consumers’ buying intention.

2.4.2. Characteristics of online reviews

Online reviews are not a simple construct, because they do not only consist of graphical and/or textual elements (Jiménez & Mendoza, 2013), but they also consist of several characteristics or factors, which will be explained in the following chapter. Considering that there are factors that make up an online review, these might also have a different effect or influence on consumers’ buying intention. Consequently this study will focus on the factors that make online reviews more influential on consumers’ buying intentions, and so therefore we will focus on the previous research regarding the characteristics of online reviews.

2.4.2.1. Scope of this study

There are several factors that make up an online review, namely the quality or strength of the reviews, language used in the reviews, short/long text reviews, number of reviews, (star) ratings, source credibility, positive/negative reviews, review platform, review platform credibility etc. We acknowledge the fact that there are several characteristics of online reviews, however because of the scope and time of this research we will not be able to focus on all characteristics. Therefore, we will focus mainly on the three characteristics, illustrated in Table 1 which we believe might be the most influential on consumers’ buying intention

namely; Number of reviews, Valence of reviews, and Source credibility. In the following subchapters these three characteristics will be explained in more detail.

Table 1. Online review characteristics that will be studied and their definition

2.4.2.2. Number of reviews

As stated by Cheung and Thadani (2012) number of reviews measures the total amount of posted online reviews (by reviewers) about a specific product or service. The research that has covered this area stated that the number of reviews can provide a reference to strengthen online shoppers’ confidence while reducing uncomfortable feelings of risk exposure, so in other words consumers may perceive that more reviews represent a more popular product and greater importance (Lin, Lee, & Horng, 2011). The study by Lin et al. (2011) they found support that large quantity of online reviews will have a positive impact on purchasing decisions. In the study by Lin et al. (2005) the majority of the participants indicated that Internet book reviews affected their buying intention, however even more so some participants found that “a large number of reviews demonstrates that a book may be of interest as it is capable of inducing discussion among readers” (p. 464).

Furthermore, Cui, Lui, and Guo (2012) found in the results of their study that the volume of reviews has a significant effect on new product sales in the early period and such effect decreases over time. Sales means of course that the product was purchased, which lets us to assume that the volume or number of reviews might also have a significant effect on

consumers’ buying intention, but to be certain this needs to be investigated. In their study Zhang, Zhao, Cheung, and Lee (2014) found that the perceived quantity of reviews positively affects behavioral intention, which they define as “consumers' willingness to purchase products or services after they process issue-relevant online reviews” (p. 81). This finding thus indicates that consumers are more likely to purchase products that have many online reviews rather than only a few online reviews (Zhang, Zhao, et al., 2014). Moreover, in the study by Lee (2009) the attitudes of online consumers increased with the number of reviews. So in the case that there were large numbers of reviews, consumers perceived it as an indication that the product is popular and consequently this might increase the purchasing intention of consumers. One of the main findings is that the quantity of reviews positively affects the purchasing intention of online consumers (Lee, 2009). In addition, in the study by Park et al. (2007) they also found that the number of reviews positively affects consumers’ purchasing intention, meaning that purchasing intentions increased as the number of online consumer reviews increased. They also state that the quantity of the reviews may be taken as representing the products’ popularity and the reason for this is because it is reasonable to assume that the number of reviews is related to the number of consumers who have bought the product (Park et al., 2007). It should duly be noted that Park et al.’s (2007) study focused on positive reviews only.

2.4.2.3. Valence of reviews (Positive vs. negative reviews)

Before discussing the valence of reviews and their effect or influence on consumers’ buying intention, it is important to define what valence of reviews is. Valence can be defined as the “Communication direction (also named as Valence, positive or negative)” (Zou et al., 2011, p. 484). Positively valenced communication is categorized by Sparks and Browning (2011) as “pleasant, vivid or novel descriptions of experiences” (p. 1312), and negatively valenced communication includes “private complaining, unpleasant or denigrating product

descriptions” (p.1312). Apart from communication being positive or negative it can also be neutral however this is less probable given that the motivation for writing about an experience is likely to be either good or bad (Sparks & Browning, 2011). In this study, a positive review is one that advises other consumers to buy the product and a negative review is a review that discourages consumers to buy a product.

The effect of online reviews on purchasing intention can be different across valence of reviews, so it can be different for positive reviews and negative reviews (Luo & Li, 2013). However, in the current literature there are no consistent findings regarding the effect of valence of reviews on consumers’ buying intention.

In the existing literature regarding the characteristic valence of reviews (positive vs. negative reviews), most research has focused on either one or the other, most of the time the focus has been on positive online reviews. An example is the study by Park & Kim (2008) in which they only focused on positive online reviews, however they also state, “although the number of positive reviews overwhelms that of negative reviews, negative reviews are influential to consumers” (p. 408). In the research by Berger, Sorensen, and Rasmussen (2010) they pointed out that negative reviews might produce positive effects, because they found that negative reviews might help companies improve product awareness and then increase consumers’ purchase likelihood. In the study by Bae and Lee (2011a) they focused on both negative and positive reviews and it was found that purchase intention of consumers is more influenced by a negative review than by a positive review. There are also some studies that argue that there is no significant relationship between the valence of online reviews and consumers’ purchasing intention (Zou et al., 2011).

However, on the relationship between the valence of online reviews and consumers’ purchasing intention there are a few studies that show an inconsistent relationship (Zou et al., 2011). East, Hammond, and Lomax (2008) found that positive online reviews had more

impact on brand purchase probability than negative online reviews. And also in their study Lin, Fang, and Tu (2010) found a positive relationship between the valence of online reviews and consumers’ purchase intention. Yet Chevalier and Mayzlin (2006) found a negative relationship between the two variables. Furthermore, as a result from the study by Zou et al. (2011) they found that the effect of negative reviews on consumers’ decision making is stronger than that of positive reviews. One possible explanation why negative reviews might indeed have a stronger effect on consumers’ buying intention than positive reviews, is because to the receiver of WOM communication, negative information has more value than positive information and so therefore consumers weight negative information more heavily than positive information (Sen & Lerman, 2007).

Interestingly enough, there is also research on valence extremity, meaning a focus on extremely negative and extremely positive reviews. In a study it was found that extremely positive agreement is more influential than negative extreme agreement (Gershoff, Mukherjee, & Mukhopadhyay, 2003). It should be noted that in the study by Gershoff et al. (2003) they looked at the acceptance of the advice agent or reviewer. In another study by Mudambi and Schuff (2010) they studied review extremity as well, however they looked at the relationship between review extremity and perceived helpfulness of the review.

Nevertheless, in the study by Lee, Rodgers, and Kim (2009) they found in both their studies that extremely positive reviews increased attitude toward the brand, but even a moderate amount of negativity cancelled out this effect. It was also found that compared to moderately negative reviews and extremely positive reviews, extremely negative reviews had a stronger influence on attitude toward the brand (Lee et al., 2009), which they argue might be because of the diagnosticity of information.

Even though extremity is an interesting additional element, in our study when talking about valence, we will focus on positive and negative reviews.

2.4.2.4. Source (reviewer) credibility

With source credibility we are not referring to the message itself, but to the consumer’s (the individual who is reading the online reviews) perception of the credibility of a message source (writer of the message/review/comment) (Cheung et al., 2008). Lee, Park, and Han (2011) stated that information from high-credibility sources is likely to be more easily accepted. With regard to the characteristic source credibility, most of the research focuses on the relationship between source credibility and information adoption, or on the relationship between source credibility and eWOM or online review credibility.

It was found in a large number of studies that credible sources compared to less credible sources result in stronger persuasion and more attitude change (Xie, Miao, Kuo, & Lee, 2011). In one of the few studies which looked at the effect of source credibility on consumers’ buying intention, they found that source credibility of online reviews, which is defined as “consumers' overall perceptions regarding the credibility of review sources, rather than the content of online reviews” (p. 82), positively affects behavioral intention (Zhang, Zhao, et al., 2014). If consumers find review sources to be credible, their purchase intention can be increased (Zhang, Zhao, et al., 2014). Furthermore, in the study by Cheung et al. (2008) they looked at the impact of online reviews and they postulated that if consumers think that a comment was posted by a highly-credible individual the consumer would then perceive the usefulness of the comments to be higher, however in their study the results were not significant.

2.5. Consumers’ demographics and lifestyle

Besides the characteristics of online reviews mentioned in the previous chapter that can influence or effect consumers’ buying intentions, there are also other variables such as consumers’ lifestyle and demographics for which the effect of those factors on buying intentions might differ. These two factors will be moderators in this study. So, what we will

study is the moderating effect of impulsiveness and gender on the relationship between some of the characteristics of online reviews on consumers’ buying intention, which is explained in the following subchapters.

2.5.1. Consumers’ gender

There are many demographic characteristics, one of which is consumers’ gender. This demographic characteristic has been proven to have a significant impact on consumers’ search behavior and information processing on the Internet (Gretzel & Yoo, 2008; Kim, Mattila, & Baloglu, 2011). Therefore, in this study when discussing demographics the focus will be on consumers’ gender.

2.5.1.1. Moderating effect of consumer’ gender

In the study by Bae & Lee (2011a) they investigated the effect of online consumer reviews on consumer’s purchase intention and in particular whether there are gender differences in responding to online consumer reviews. They found that the effect of online consumer reviews on purchase intention is stronger for females than males and females are influenced more by negative reviews than positive reviews (Bae & Lee, 2011a). Fan and Miao (2012) show in their study that gender differences affect perceived eWOM credibility, use and acceptance of eWOM, and purchasing decisions and their results also show that male customers have different e-commerce shopping behaviors than female customers. According to Fan and Miao (2012) female consumers may perceive more risk when shopping online and as a result they may be more reluctant to make purchasing decision compared to male consumers. Moreover, in the study by Zhang et al. (2014) female consumers are found to be more responsive to a mix of positive and negative reviews, thus, are more prone to shop online than males in such circumstance. The findings from the study by Kim et al. (2011) further indicate that men are less likely to read reviews for convenience and quality than are

women. They further explain that women are more likely to read reviews for the purpose of convenience, quality, and risk reduction, but the use of online reviews among men is depended on their level of expertise in online hotel bookings (Kim et al., 2011). Furthermore, Gretzel and Yoo (2008) found that there are gender differences for the perceived impacts of reviews, especially in terms of enjoyment and idea generation; females gain greater benefits from using online reviews.

2.5.2. Consumers’ impulsiveness

To start, we would first like to examine what is meant with consumers’ lifestyle. Kotler and Armstrong (2008) define lifestyle as “a person’s pattern of living as expressed in his or her psychographics” (p.140) that can affect buying behavior. As stated by Kim, Cho, and Rao (2000) "individual characteristics such as a consumer’s lifestyle need to be emphasized as key determinants of purchasing decisions” (p.689). Swinyard and Smith (2003) examined in their study the lifestyle characteristics of online households, and they found that online shoppers are younger, wealthier, better educated, have higher computer literacy, spend more time on their computer, spend more time on the Internet, find online shopping to be easier and more entertaining, and are more fearful of financial loss from online shopping.

2.5.2.1. Moderating effect of consumers’ impulsiveness

There is very little research and knowledge on consumers’ lifestyle and the relationship between this variable and online reviews or consumers’ buying intentions. Most of the current literature is focused on consumers’ lifestyle and their online shopping behavior. For this reason we decided to have a look at the consumer lifestyle trait, impulsiveness (Muruganantham & Bhakat, 2013), more specifically to consumers’ impulse purchasing.

Consumer impulse purchase can be defined as “an unplanned action that results from a specific stimulus” (Ling et al., 2010, p. 63). Impulse purchase takes place whenever consumers experience an unexpected urge to purchase something immediately, “lack

substantive additional evaluation, and act based on the urge” (Ling et al., 2010, p. 65). In addition, Kacen and Lee (2002) explained impulsive buying to be "a sudden, compelling, hedonically complex purchasing behavior in which the rapidity of the impulse purchase decision process precludes thoughtful, deliberate consideration of all information and choice alternatives" (p. 163).

Existing literature states that impulse purchase will positively affect online purchase intention (Zhang, Prybutok, & Strutton, 2007). In both studies by Zhang et al. (2007) and Ling et al. (2010) they concluded that impulse purchase is positively related to consumers’ online purchase intention. So, from current literature it is not clear whether impulsiveness has a moderating effect on the relation between the factors of online reviews and buying intention.

Table 2.!Review of online reviews’ characteristics on consumers' buying intention literature and effect of gender and impulsiveness !

Articles Online reviews

Characteristics Demographics and

Lifestyle Buying intention Number of reviews Valence of reviews Source credibility Gender Impulsiveness Lin et al. (2011)

✔ ✔ ✔ (Positive impact number of reviews on consumers’

buying intention) Cui et al.

(2012)

✔ ✔ Volume of reviews significant effect on new product

sales, no mention of consumers’ buying intention Zhang, Zhao,

et al. (2014)

✔ ✔ ✔ (Perceived quantity of reviews positively affects

consumers’ willingness to buy)

✔ (Source credibility positively affects consumers’ willingness to buy)

Lee (2009) ✔ ✔ (Quantity of reviews positively affects purchase

intention of consumers) Park et al.

(2007)

✔ ✔ (Number of reviews positively affects consumers’

purchasing intention) Park & Kim

(2008) ✔ (Focused on positive reviews only)

Effects of consumer knowledge on message processing through online reviews

Bae & Lee (2011a) ✔ ✔ (Focused on both positive and negative reviews)

✔ ✔ (Purchase intention of consumers is more influenced by a negative review)

✔ (Online consumer reviews’ effect on purchase intention is stronger for females)

East et al. (2008)

✔ ✔ (Positive online reviews had more impact on brand

purchase probability) Lin et al.

(2010)

✔ ✔ (Positive relationship between the valence of online

reviews and consumers’ purchase intention) Chevalier &

Mayzlin (2006)

✔ ✔ (Negative relationship between the valence of online

reviews and consumers’ purchase intention) Zou et al.

(2011)

✔ ✔ (Negative reviews have a stronger effect on

consumers’ decision making) Several

studies (Xie et al.,

2011)

✔ Credible sources compared to less credible sources result in stronger persuasion and more attitude change

Cheung et al. (2008)

✔ No significant results were found regarding source credibility on consumers’ buying intention

Zhang et al. (2014)

✔ Find that female consumers are more responsive to mix of positive and negative reviews, thus, are more prone to shop online. No mention of consumers’ buying intention

Kim et al. (2011)

✔ Findings are about comparing reading of online reviews between men and women, no mention of consumers’ buying intention

Gretzel and Yoo (2008)

✔ Females gain greater benefits from using online reviews, no finding about their buying intentions Zhang et al.

(2007)

✔ ✔ (Impulse purchase is positively related to consumers’ online purchase intention)

Ling et al. (2010)

✔ ✔ (Impulse purchase intention is positively related to consumer online purchase intention)

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2.6. Literature Gaps and Research question

Although current literatures have been conducted to examine the relationship between online reviews and consumers’ buying intention, little is known about the specific relationship between valence of reviews and consumers’ buying intention. On the effect of valence of reviews (positive vs. negative reviews) most research have looked at one or the other, in this study we want to see the effect of both kinds of reviews on consumers’ buying intention. In addition, just as mentioned by Zou et al. (2011), the findings are inconsistent regarding the relationship between the two variables.

With regard to the source credibility characteristic of online reviews, its effect on consumers’ buying intention needs to be examined, since the studies that have been conducted did not research its effect on buying intention, and the study that did research its effect found that their results were not significant (Cheung et al., 2008). Moreover, regarding the moderating variables consumers’ gender and impulsiveness, little is know about how the effect of the number of reviews and valence of reviews on consumers’ buying intention will differ for male consumers compared to female consumers, and impulsive consumers.

Table 3. Gaps in the current literature

! So overall, this study is aimed at closing the gaps (Table 3) in the existing literature about the effect of online reviews characteristics on consumers’ buying intention, and to what

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extent that effect differs across consumers’ lifestyle and demographics, with the research question being: “What are the factors related to online reviews that are more influential on consumers’ buying intention and which demographic and psychographic factors affect this relationship?”

2.7. Theoretical and managerial contribution

This research contributes to the current literature in the following ways. First, by focusing in this study on the effect of both positive and negative reviews on buying intention, we will be adding to the current knowledge of the effect of valence of reviews on consumers’ buying intention. Second, one of the independent variables in our study is source credibility and we will be contributing to the current literature in the form of trying to find an effect on consumers’ buying intention seeing as little is known and in studies where they tried studying this effect, no significant results were found. Third, as we noticed from the existing literature, the effect of the number of reviews and valence of reviews on male/female consumers’ buying intention is not well studied, but we will attempt to do this in our study. Lastly, regarding impulsive consumers little is know about whether the number of reviews is influential on their buying intention, and this is exactly what our study will add to the existing literature.

With this research it is the purpose to contribute to firms and managers in the following ways. First, online reviews are necessary for companies to attract and retain consumers according to Schlosser (2011), but simply offering online reviews is not enough. So it is important to understand what makes online reviews more influential. Therefore, the effect of three characteristics of online reviews on consumers’ buying intention will be tested. An understanding of the characteristics of online reviews on buying intention is important for firms and managers because online reviews as we know are an important source of communication for consumers. It is a way for them to express what they feel or think about a

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product or service. By having a better understanding of the characteristics of online reviews and their effect on consumers’ buying intention, firms and managers might be better able to communicate with their (potential) consumers about their products or services. Therefore it is important to know which characteristics of online reviews are the most influential on consumers’ buying intention. Also, firms could for example allocate more resources on creating online reviews or encouraging consumers to create more online reviews. Depending on the characteristics of online reviews that are found to be the most influential on consumers’ buying intentions, a firm can play into those characteristics to try and have a greater effect on their consumers’ buying intentions.

Furthermore, the effect of the characteristics of online reviews on consumers’ buying intention might differ for other factors as well, such as consumers’ impulsiveness. It might be the case that for impulsive consumers, so consumers who do not plan their purchases, purchase spontaneously or who do not spend as much time looking for information regarding a product (Kacen & Lee, 2002), that the effect of the characteristics of online reviews might have a different impact on their buying intention. By understanding what the effect is on the buying intention of impulsive consumers, firms and managers can allocate means to target them in a specific or strategic way. In addition, the effect of the characteristics of online reviews might also be different for female or male consumers. By knowing these differences companies can make use of online reviews in the most effective way by making decisions or setting up strategies targeting those specific consumers.

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3. CONCEPTUAL FRAMEWORK

! Figure&3.&Conceptual&framework&

Note: Online reviews related factors are only a dimension in consumers’ buying intentions. There are many other factors such as, perceived service, product quality, brand image etc., which also have an impact on buying intentions. However, within the scope of our study we do not capture them in our analysis and solely focus on online reviews and their effect.

Figure 3 provides an overview of the conceptual framework of this study. This conceptual framework has been developed to test the hypotheses, which are mentioned and explained in the following subchapter. In addition, the framework has also been developed to analyze the effect of number of reviews, valence of reviews and source credibility on consumers’ buying intention. Also, to see whether the latter effect would differ across consumers’ demographics (gender) and consumers’ lifestyle (impulsiveness). How data is collected is explained in the next chapter.

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3.1. Hypotheses

As mentioned before, online consumer reviews are a specific type of eWOM that can be defined as peer-generated or consumer-created product evaluations (Jalilvand et al., 2011; Mudambi & Schuff, 2010). Buying intention can be seen as a measure of the possibility that a consumer will purchase/buy a product, meaning that the higher the purchase intention expressed, the greater the possibility and probability that the consumer will actually buy the product (Schiffman & Kanuk, 2000). Based on the several findings that online reviews do affect consumers’ purchase intention (Cheung & Thadani, 2012; Zhang et al., 2014; Gretzel & Yoo, 2008; Lee & Kwon, 2008) it is expected that online reviews will have a positive effect on consumers’ buying intention, however we are more interested on the effect of the characteristics of online reviews on consumers’ buying intention.

Online reviews consist of several elements or characteristics, and these characteristics might have a different effect on consumers buying intention, some might be more influential then others. As we have mentioned in a previous chapter, we will only be focusing on three of those characteristics, which we believe will be the most influential on consumers’ buying intention namely; Number of reviews, Valence of reviews (positive vs. negative reviews), and Source credibility.

Number of reviews as we know measures the total amount of posted online reviews (by reviewers) about a specific product or service (Cheung & Thadani, 2012). One research on the effect of number of reviews found that the volume of reviews has a significant effect on new product sales, but they did not look at the effect on consumers’ buying intention (Cui et al., 2012). Nevertheless, there are many other studies, such as the study by Lin et al. (2011), Zhang, Zhao et al. (2014), Lee (2009), and Park et al. (2007), in which they all found that the number of reviews positively affects consumers’ buying intention. This indicates that as the number of reviews increases or becomes larger, the consumers’ buying intention increases as

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well. Because of the findings that a large number of reviews can lead consumers to perceive that a product is popular and that this perception consequently increases the purchase intention of consumers, it is expected that the number of reviews will have a effect on consumers’ buying intentions. Therefore, we hypothesize the following hypothesis:

H1. The number of reviews has an effect on consumers’ buying intention

Valence of reviews refers to the direction of the communication, which can be positive or negative (Zou et al., 2011). There might be a great variety in terms of what is perceived as positive or negative in online reviews. Therefore, for the purpose of this study we will keep to a simpler explanation, a positive review is one that advises other consumers to buy the product and a negative review is a review that discourages consumers to buy a product.

The effect of online reviews on purchasing intention can be different for positive and negative reviews (Luo & Li, 2013). However, in the current literature there are no consistent findings regarding the effect of valence of reviews on consumers’ buying intention, some find a positive relationship between the variables such as the study by East et al. (2008), and others find a negative relationship (Chevalier & Mayzlin, 2006). In addition, negative reviews are found by Zou et al. (2011) to have a stronger effect than positive reviews on consumers’ decision making. A plausible reason behind this effect is that negative information has more value than positive information and so therefore consumers weight negative information more heavily than positive information (Sen & Lerman, 2007).

Even though the findings on valence of reviews on consumers buying intention are inconsistent, we expect that valence of reviews will have an effect on buying intention. Therefore, we hypothesize that:

H2. Valence of reviews will have an effect on consumers’ buying intention

The characteristic source credibility refers to consumer’s (the individual who is reading the online reviews) perception of the credibility of a message source (writer of the

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message/review/comment) (Cheung et al., 2008). Most of the studies on source credibility postulate that the higher the source credibility, the higher the consumers’ intention to buy. One study found evidence that source credibility affects consumers’ purchasing intention however, another did not find a significant result. Nevertheless, we also expect that the higher the source credibility of the online review is perceived to be, the higher the consumer’s buying intention will be. Therefore we developed the following hypothesis:

H3a. Source credibility will have an effect on consumers’ buying intention.

In our study we plan on showing the participants information about the source of the online review, so the reviewer. Their name will be shown, their ranking and the percentage of helpfulness their reviews have received. So besides looking at the effect of source credibility on consumers’ buying intention, we are also interested in finding out whether the Reviewer’s ranking or the Reviewer’s percentage of helpfulness makes the source more credible. So, we developed the following hypothesis:

H3b. The reviewer’s percentage of helpfulness will be found to be more credible than reviewer’s ranking.

Beyond the characteristics of online reviews mentioned that can influence or effect consumers’ buying intentions, there are also other variables such as consumers’ lifestyle and demographics for which the effect of those factors on buying intentions might differ. The focus in this study will be on consumers’ gender, because it has been proven that this specific demographic characteristic has a significant impact on consumers’ search behavior and information processing on the Internet (Gretzel & Yoo, 2008; Kim et al., 2011).

When reading online reviews it has been found that a difference exists between males and females. Females are more likely to read online reviews than men for convenience, quality, and risk (Kim et al., 2011). In addition, females gain greater benefits from using online reviews (Gretzel & Yoo, 2008). Even though it was found that females are more

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responsive to a mix of positive and negative reviews than men (Zhang et al., 2014), we believe that because negative reviews can be seen as more valuable female consumers might weight negative information more heavily than positive information (Sen & Lerman, 2007), seeing as they read online reviews for quality and risk.

So, we expect that because negative reviews might be weighed more heavily and women seek to read online reviews for the purposes of convenience, quality, and risk, that the valence of the review would have a greater effect on their buying intention. For that reason we developed the following hypothesis:

H4a. The effect of valence of reviews on buying intention will be greater for female consumers than male consumers

As we know men do not read online reviews for convenience, quality, or risk, their use of online reviews depends on their level of expertise on that product or service (Kim et al., 2011). However, little is know about how the effect of number of reviews on consumers’ buying intention differs for males and females. Because men are less likely to read online reviews for convenience and quality (Kim et al., 2011) and because we believe less effort needs to be put in by the consumer when considering the number of reviews (compared to reading online reviews), we expect that the number of reviews will have a greater effect on men’s buying intention. Therefore we hypothesize that:

H4b. The effect of the number of reviews on buying intention is greater for male consumers. Impulsiveness is a consumer lifestyle trait (Muruganantham & Bhakat, 2013) and it can be seen as an unexpected urge to purchase something on the spot (Ling et al., 2010). Studies have found that impulse purchase positively affects purchase intention (Zhang et al., 2007; Ling et al., 2010). However, none of the studies have focused on whether the effect of number of reviews and valence of reviews will differ for impulsive consumers. Therefore, the final hypothesis in our study is concerning impulsive buying consumers. Consumer impulse

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purchase can be explained as an unplanned purchase that takes place when consumers feel a kind of urge to buy a product or service, it lacks additional evaluation (Ling et al., 2010), and the purchase precludes deliberate consideration of all information (Kacen & Lee, 2002).

From the explanation of impulsive buying and its found effect on consumers’ buying intention, we presume that because impulsive consumers do not think, deliberate, or consider all information and choice alternatives (Kacen & Lee, 2002), they will be less likely to read online reviews. So, we believe that because the number of reviews characteristic does not require as much deliberation (as reading an online review), we expect that the number of reviews will be more influential on impulsive consumers’ buying intention. Therefore, we hypothesize that:

H5. The effect of the number of reviews on buying intention will be greater for impulsive consumers.

Table 4. Hypotheses

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4. RESEARCH DESIGN AND METHODOLOGY

To investigate the effect of online reviews characteristics/factors on consumers’ buying intention, as well as how this effect might differ among male, female, not impulsive, and impulsive consumers, so to be able to test the hypotheses proposed, data is collected. This chapter describes how data was collected. In the first part of this chapter, the sample of this study is described. In the second part of this chapter, the research design is described including explanation about the experimental survey that will be used and the measures, the measure items, and variables are clarified. In the third and last part of this chapter, the procedure about how data will be collected is described.

4.1. Sample

The shopping consumers in the Netherlands, who have Internet access, will be the population of this study. In the Netherlands there are approximately 12.3 million Internet users (CBS, 2013) and 83% of the Internet users (between ages 18 and 75) indicated that they shopped online, which is approximately 10.3 million people (CBS, 2014). The most active online shoppers are young adults under the age of thirty (Bae & Lee, 2011b), however older people are also using the Internet as stated by the CBS (2014). Therefore, the population of this study will be shopping consumers in the Netherlands between the ages of 18 and 75. As for the sample selection method, non-probability sampling will be used, because no sampling frame could be retrieved for the enormous research population. The non-probability sampling technique will be quota sampling and will be distributed via social media and e-mail.

To increase the chance of having a representative sample and to be able to generalize the conclusions of this study over the population, the main goal for data collection will be to achieve a sample as large as possible. The minimum sample size will consist of data from at

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least two hundred and forty (240) shopping consumers in the Netherlands, which is 30 participants per treatment (Saunders & Lewis, 2012).

On April 19, 2015 the Experimental survey was distributed and it was deactivated on April 30, 2015. In total 429 questionnaires has been filled in, subsequently 116 of these have been deleted due to insufficient or non-answered questions. Thus, in total 313 questionnaires were used during the analysis. From the 313 participants, 152 were male (49%) and 161 were female (51%). Most of the participants were between the ages 18 and 29. The youngest participant was 18 years old and the eldest participant was 72 years old.

4.2. Research design

To be able to identify and explain the effect of online reviews’ characteristics (number of reviews, valence of reviews, and source credibility) on consumers’ buying intention, and to test whether the latter effect differs among male, females, impulsive, and not impulsive consumers, a quantitative research through an online experiment (experimental survey) was most appropriate. The reason for choosing an online experiment is because web experiments offer (1) easy access to a diverse demographic and cultural participant population; (2) cost savings in terms of lab space, person-hours, equipment, and administration; and (3) a large percentage of participants will remain in their familiar situation, such as for example at their computer at home or at work, increasing the external validity of the study (Reips, 2000). In addition, statistical analysis can be done to compare a diversified and large sample of respondents (Saunders & Lewis, 2012). It should be noted however that the dependence on technical interface might limit external validity of online experiments, but because of the “wide variety of situations that allow for access will increase external validity in online experiments” (Reips, 2000, p.9). Moreover, it is worth noting that several other studies have used online experiment as well in their researches (Lin et al., 2011; Bae & Lee, 2011a; Senecal & Nantel, 2004; Bae & Lee, 2011b; Lee, 2009).