THE DIFFERENTIAL EFFECT OF
QUALITATIVE REVIEW VALENCE ON
WILLINGNESS TO PAY: THE
MODERATING EFFECT OF PRICE
ANCHORING
by
Jordi Zaoudi
THE DIFFERENTIAL EFFECT OF QUALITATIVE REVIEW VALENCE
ON WILLINGNESS TO PAY: THE MODERATING EFFECT OF PRICE
ANCHORING
University of Groningen Faculty of Economics and Business
Department of Marketing MSc Marketing Management
Master thesis 26-07-2018
J. (Jordi) Zaoudi Zwolle, The Netherlands
0643460815 J.Zaoudi@student.rug.nl Student number S2281090
Supervisors: R.P. (Roelof) Hars prof. dr. L.M. (Laurens) Sloot
ABSTRACT
The aim of this study is to investigate the influence of price anchoring in the effect of review valence on willingness to pay. Since online reviews are important for both customers and companies, as customers use this information to evaluate products and companies use reviews to influence customers' purchase decisions. This study focuses on the influence of a positive, neutral or negative review text (qualitative) on willingness to pay and the effect of price related expressions (price anchors) in this review text. We hypothesize that price anchoring strengthens the positive relationship between qualitative review valence and willingness to pay. Our hypotheses were tested by means of a questionnaire in which Dutch consumers filled in their willingness to pay after reading a negative, neutral or positive review. The effect of price anchoring was measured by using price related expressions, e.g. 'cheap' or 'expensive', in the content of a review. The findings showed that qualitative review valence was positively related to willingness to pay, so customers were willing to pay more in case of a positive review than for a negative or neutral review. However, the effect of price anchoring was only partly significant. The article concludes with theoretical and managerial implications.
TABLE OF CONTENTS
INTRODUCTION 4
THEORETICAL FRAMEWORK 7
Qualitative review valence 7
Willingness to pay 7
The relationship between qualitative review valence and willingness to pay 8
Price anchoring 10
The moderating effect of price anchoring 11
Conceptual framework 13
RESEARCH DESIGN 13
Sample and procedures 13
Measurements 14
Analytic approach 17
RESULTS 18
Descriptives 18
Qualitative review valence and willingness to pay 19
Main effect - Age, online shopping experience & product knowledge 20
The effect of price anchoring 21
DISCUSSION AND CONCLUSIONS 23
Summary of results 23
Managerial implications 25
Limitations and future directions 26
REFERENCES 27
APPENDIX A - Control variables 33
APPENDIX B - Further analysis 34
INTRODUCTION
Nowadays, almost everyone reads customer reviews before purchasing a product. Online customer reviews have become important for customers, as customers use the information to evaluate products before they decide to purchase these products (Cui et al., 2012). For companies, making use of online product reviews is an effective way to influence customer decisions. Online product reviews have a great impact on customer experience, as these reviews influence the customer experience before actually purchasing a product, during the purchase and after the purchase (Lemon & Verhoef, 2016; Baxendale et al., 2015). The information provided by other customers has more value for these customers than information provided by the company that sells the product (Blazevic et al., 2013). That online customer reviews are practically relevant is also underscored in previous studies (e.g., Chevalier & Mayzlin, 2006). So it is important to learn more about the effects of online reviews.
The relevance of using positive, neutral and negative qualitative reviews, in which customers freely describe their experiences in written statements (Sridhar & Srinivasan, 2012), has been emphasized by previous research. Research indicates that customers attach more value to text valences, compared to rating valences, when the interestingness is being considered. The reason for this is that customers need to have enough information to change their perceptions, ratings only summarize the experiences (Tsang & Prendergast, 2009). Also, much has been written about the effect of positive reviews, however negative reviews seem to have more influence in the buying decisions customers make (Bambauer-Sachse and Mangold, 2011; Sen and Lerman, 2007). Positive reviews are about the favorable experiences with certain products or services and negative reviews are written to express disappointing experiences. Companies are trying to avoid negative reviews on their website, as this can be very harmful for their reputation and sales (Bambauer-Sachse and Mangold, 2011).
Customers may not only leave negative and positive reviews, but also neutral reviews that contain both negative and positive aspects (Book et al., 2016). Using qualitative customer reviews in this research could give us new and interesting insights (Kostyra et al., 2016).
consequence, companies aim at a high willingness to pay to increase their profits.
Willingness to pay indicates the maximum monetary value that customers are willing to pay for a product or service (Homburg et al., 2005). Previous studies have shown that review valence has a positive effect on willingness to pay for different product types in retailing, e.g. stamps (Dewan & Hsu, 2004) and comic books (Dewally & Ederington, 2006). However, the effect of review valence on willingness to pay isn't as consistent as we might think. Previous studies have also shown mixed results regarding the effects of review valence on willingness to pay (Wu & Gaytán, 2013; Zhu & Zhang, 2010).
A study by Resnick et al. (2006) showed that review valence for postcards didn't have an effect on willingness to pay. In their study they added one or two negative reviews to a seller that already had positive reviews and found that this didn't affect the willingness to pay in terms of a price penalty. Other studies showed that online reviews on its own did not influence sales/profits, because consumers were only influenced by the number of posts and not the persuasiveness of the review (Chen et al., 2004; Duan et al., 2008). The effect of online reviews on willingness to pay depends, amongst other things, on product type, review volume, review helpfulness, customer characteristics and attitudes (King et al. 2014; Wu et al., 2013). A number of these variables can be linked to a cognitive bias called the 'anchoring effect', as variables like mood, knowledge, motivation, personality and cognitive ability are important factors considered in the anchoring literature (Furnham & Boo, 2011). In turn, price anchoring has shown to be a key determinant of willingness to pay (Simonson & Drolet, 2004). So, the effect of price anchoring could be a possible explanation for the
inconsistencies that prior research found in the effect of online reviews on willingness to pay. Anchoring occurs when "...different starting points yield different estimates, which are biased toward the initial values" (Tversky & Kahneman, 1974). The anchoring effect entails that customers use information that is given to them in the decision making process as 'anchor' to determine the value of a product, their initial standard is biased towards an
participant. In a study by Kuijken et al. (2017) the anchoring effect, of the average value of a product category, only occured when the product was radically innovative and not for
products that are incrementally innovative. The reason for this is that customers have less knowledge about relatively new products, so customers are more likely to use externally provided price anchors. Thus, research has shown that different types of anchors can have different effects (Wansink et al., 1998; Dogerlioglu-Demir & Koçaş, 2015; Lin & Chen, 2017). It would be interesting to incorporate price anchoring in a content analysis of online reviews as customers are actively seeking for price information (Wu et al., 2013). Examining the effects of favorable, neutral or negative expressions in online reviews regarding the price perception could provide us with interesting information, as research has shown that the decision-making process can be influenced by the way information is presented (Wu & Cheng, 2011).
This study aims at discovering the relationship between qualitative review valence and willingness to pay with the influence of anchors that are provided by an external source (Epley & Gilovich, 2001). Thus, the effect of anchoring in the content of a review will be analyzed. The anchors are related to price perception and will be provided by other people who express themselves by writing an online review. 'Cheap' and 'expensive' are examples of anchors in this study. These words are related to semantic anchoring (Carroll et al., 2009), the words can be placed on a scale from best to worst or cheapest to most expensive and are relative to a price anchor. It is important for companies to know whether and to what extent these price anchoring words affect the willingness to pay, because companies also use these words, for example, in a summary of all the reviews on a product page. Anchoring has a remarkable effect on judgment and decision making and its effect is robust
(Dogerlioglu-Demir & Koçaş, 2015), which makes it an interesting effect for further research. So, the effect of online reviews on willingness to pay is still an important research area, as previous studies showed different results and research on willingness to pay could give direct implications for management. Price anchoring is an underlying process that
willingness to pay. Also, online reviews have become very important in influencing
customers. Thus, we have to learn more about the phenomenon of price anchoring in online reviews and its influence in the effect of review valence on willingness to pay. The aim of this study is to fill the research gap of this specific relation and to be able to give clear practical implications for management. The problem statement leads to the following research question:
How strong are the different effects of negative, neutral and positive qualitative consumer reviews on the willingness to pay and how does price anchoring in the content of a review
influence this effect?
The paper at hand starts with the theoretical framework, in which existing literature will be discussed followed by the conceptual model and hypotheses. Then the research design is introduced, in this section the research method, data collection and analytic approach will be explained. After that, the results will be shown and interpreted. The paper ends with
conclusions based on the research results and the recommendations, limitations and future research directions will be discussed.
THEORETICAL FRAMEWORK
Qualitative review valence
As explained in the introduction, this study focuses on qualitative reviews. The content of the reviews shows that there are three types: negative, neutral and positive reviews (Book et al., 2016). Qualitative reviews are written statements of the negative, neutral or positive
experiences that customers have with a product (Jiménez & Mendoza, 2013). Customers can freely describe their negative, neutral or positive experiences in these written statements (Sridhar & Srinivasan, 2012).
Willingness to pay
research (Grewal et al., 2010). Willingness to pay can be defined as the highest price that a customer wants to pay for a certain product, it is the maximum at which a consumer will definitely buy the product (Le Gall-Elly, 2009). Consumers' willingness to pay can be seen as a point measure (Wu & Wu, 2016). Willingness to pay is also called reservation price and is a measure expressed in a monetary value that is assigned to the product by a customer. This value is not as abstract as terms like loyalty and purchase intentions, but it gives companies an absolute measure that can be used in pricing strategies (Homburg et al., 2005).
The relationship between qualitative review valence and willingness to pay
The influence of qualitative review valence and willingness to pay is now going to be
discussed. Previous studies have shown that the influence of online reviews on willingness to pay can be very different under different circumstances and with different factors influencing this relationship (Weisstein et al., 2017). The study outcomes that are relevant to the effect of qualitative online reviews on willingness to pay will be discussed.
Several studies have shown that review valence positively influences the willingness to pay. According to Chevalier and Mayzlin (2006), book sales are significantly influenced by online reviews and customers prefer to read the text of a review instead of just taking a look at the summary statistics. They also found that negatively valenced reviews have a significantly negative effect on sales and positively valenced reviews are positively related to sales. Tang et al. (2014) also concluded that negative (positive) reviews result in a negative (positive) attitude toward a product. Other studies showed that variance and volume do not influence sales, but that the valence of a review does influence the sales positively and indicate that we should attach more importance to research on review valence (e.g. Moe & Trusov, 2011; Jang et al., 2012). Kostyra et al. (2016) found that the willingness to pay increases when the valence of an eBook reader review positively increases. They argue that low-valence products discourage customers to buy the product, as customers attach a lower value to the product based on the low valence, and high-valence products increase the willingness to pay.
However, previous research also indicates that the effect of online reviews on
experience products, which are difficult to evaluate in advance. They found that the credibility of a review for search products is affected by the level of detail, which is the amount of specific information in the content of a review. The credibility of a review for experience products is affected by reviewer agreement, which is the degree of perceived agreement among the reviewers of a product. A study by Duan et al. (2008) showed that a higher rating didn't result in an increase in sales. Instead of review valence the review volume had an effect on sales, which implies that customers are not always influenced by the review valence. The results of a study by Wu et al. (2013) showed that the effect of review volume and variance can be negative, insignificant or positive and that the effect depends on the risk attitudes of customers. Zhu and Zhang (2010) take the customers' internet experience into account and find that the sales of games for which players have more internet experience are more influenced by online reviews.
Negative information seems to have more influence in decision making than positive information (Book et al., 2016). This can be explained by the prospect theory, which
indicates that consumers attach more value to preventing losses than acquiring gains. The reason for this is that people prefer a single gain over a potential loss, because certain outcomes are more important than merely probable outcomes. People are more afraid of losing their current wealth and less concerned to gain (Kahneman & Tversky, 1979).
According to Bambauer-Sachse and Mangold (2011) the effect of a negative online review is only strong for customers with a purchase goal. Moreover, the results of a previous study (Ren et al., 2018) have also shown that negative reviews can lead to an increase in sales, so negative reviews do not always imply that sales will decrease. They found that an increase in the number of reviews (volume) is more important than (negative) review valence, as
customers' awareness of a product will increase because of an increase in volume. In return, this leads to an increase in sales and implicates that companies shouldn't try to manipulate review valence (Ren et al., 2018). The result of their study is remarkable, because most studies show that negative online reviews lead to a decrease in sales (e.g. Chevalier & Mayzlin, 2006).
are also related to price anchoring (Furnham & Boo, 2011), which will be discussed further in the next section about price anchoring. As the results of most of the prior studies that were discussed showed that online reviews have a positive effect on sales or willingness to pay (e.g. Wu et al., 2013; Kostyra et al., 2016), we expect that qualitative review valence will positively influence the willingness to pay in this study.
H1: Qualitative review valence is positively related to willingness to pay
Price anchoring
The moderator is price anchoring. In the introduction of this study the pioneering work on anchoring by Tversky & Kahneman (1974) was already mentioned. Based on their study, research on the anchoring effect has grown extensively (Furnham & Boo, 2011). The basic assumption of price anchoring is that judgment is influenced by a reference point (anchor), so that customers' value judgment is adjusted from the initial value (Tversky & Kahneman, 1974). An anchoring effect is produced when the adjustment is insufficient (Epley &
Gilovich, 2001). Anchors can be self-generated, which is often the case, but they can also be externally provided.
Most people know the anchoring effect from marketing (e.g. sales in stores), where it is used to make people belief that they bought a much better deal. For example, a store could set the price of a product too high, so this price would serve as an anchor. Then, the store advertises a lower price (or regular/market price), which will make customers feel like they've got a much better deal because of the perceived discount. However, previous studies have shown that the anchoring effect doesn't always rely on numeric anchoring (e.g. product prices), but also non-numeric anchors can cause the anchoring effect. For example, a study by Oppenheimer et al. (2008) has shown that physical anchors can influence numeric targets, e.g. willingness to pay in our study. In another study, by Kruger (1999), a person's own skills served as anchor. The results were consistent with the anchoring and adjustment
possibly increase or decrease the value estimation of a product when people who read a review are exposed to these anchors, which could be an automatic and effortless process (Kruger, 1999).
The moderating effect of price anchoring
There is limited research about the effect of price anchoring in an online review context. To the best of our knowledge, the effect of price anchoring in the relationship between
qualitative review valence and willingness to pay hasn't been researched yet. However, the anchoring effect is related to price (perceptions) and has been studied in many other relations (e.g. Furnham & Boo, 2011; Wu and Cheng, 2011; Dogerlioglu-Demir & Koçaş, 2015). So, we argue that price anchoring can influence the relationship between qualitative review valence and willingness to pay.
Lin and Chen (2017) found that the anchoring effect only occurs when consumers find the price anchor credible, they find the price anchor credible when it fits to their distribution of their internal reference price. So, customers compare it to their internal reference price and they will not use it as price anchor when the price information is far different from their estimate. The internal reference price is based on information stored in memory obtained by prior purchases, for which the previously observed price of the product is the most important factor. They also showed that the willingness to pay increases
(decreases) when the price information, that is offered externally, is higher (lower) than the internal reference price. So, online reviews can adjust the internal reference price, as these reviews offer the external information.
This effect will be even stronger when people obtain direct information (price
which was a consequence of so-called "direct risk aversion". The uncertainty effect means that a worse possible outcome is valued higher than a risky prospect. The reason for this is that people are directly influenced by the feeling of uncertainty, which is called direct risk aversion. This suggests that using price anchors in the content of a review could reduce uncertainty regarding the reference price, as these price anchors give direct and more certain information about the accuracy of the reference price. Consumers are actively seeking for price information in the content of a review (Wu et al., 2013). Thus, price anchors can strengthen the change in reference price, when the person who wrote the review states that the price should be lower/higher.
The results of a study by Book et al. (2016) indicated that price anchoring has a different effect in positive and negative review situations. In this study price anchoring had more influence in a situation with positive reviews than a situation with negative reviews and showed no significant effect in their experiment with negative reviews. The reason for this is that processing negative information requires more effort, because negative information is more salient than positive information. This is consistent with the earlier discussed prospect theory (Kahneman & Tversky, 1979). Customers are likely to attach more value to negative reviews, so these negative reviews seem to be more important than price information (Book et al., 2016). However, this conclusion is based on price information, in absolute values, that is provided outside of the content of the online review. It would be interesting to know whether this conclusion also holds when we use price anchors within the content of the review and compare the effect for negative, neutral and positive reviews.
Based on the results of previous studies, we expect that price anchoring will play an important role in this study. Price anchoring could strengthen the relationship between online reviews and willingness to pay, as it gives people certainty about the height of the reference price. This leads to the second hypothesis, which states that price anchoring strengthens the positive relationship between qualitative review valence and willingness to pay. Furthermore, it will be interesting to know how and to what extend price anchoring moderates this
relationship.
Conceptual framework
Based on the discussion that leads to two hypotheses, the conceptual framework of this study is shown in figure 1. H1 represents the relationship between qualitative review valence and willingness to pay, for which we expect that qualitative review valence is positively related to willingness to pay. H2 entails the moderating effect of price anchoring in the relationship between qualitative review valence and willingness to pay, as we expect that price anchoring strengthens this relationship.
Figure 1: Conceptual framework
RESEARCH DESIGN
Sample and procedures
The aim of this research is to determine the effect of qualitative review valence (IV) on willingness to pay (DV) and the effect of price anchoring in this relationship. A qualitative research, in the form of a questionnaire, is performed for this study. The survey was made by using Qualtrics, online survey software, and data was collected by using the online link for the survey. The questionnaire can be found in Appendix C. The questionnaire was filled in at one specific moment in time. For the data collection we focused on Dutch consumers, which was the target group of this research. Data was collected by sharing the online survey on social media (e.g. Facebook) and by approaching family, friends, colleagues and other people. So we used convenience sampling, because it's a good way to gather many
distribute this survey to other consumers more data was collected. To increase the response rate and reduce a possible loss of motivation, we kept the questionnaire simple and short. Also, respondents were offered a chance to win a €25 gift card if they filled in all the questions.
Measurements
To measure the differential effect of review valence and the anchoring effect at the individual level, the study format was a within-subject approach (Wu & Gaytán, 2013). The willingness to pay could differ per respondent, but as we use a within-subjects design we were able to compare the results. In a between-subjects design different groups of subjects are exposed to different treatments, so subjects would be less aware of the manipulation in the experiment. However, the within-subjects design was used to control for individual differences between the subjects, so every respondent was exposed to every condition (Malhotra, 2010). Every subject serves as his own control, which should give this design more power compared to a between-subjects design. This design is also used in previous research that measured the willingness to pay for different situations (e.g. Wu et al., 2013; Simonson & Drolet, 2004). In line with previous research that studied the effect of customer review valence (e.g. Wu & Gaytán, 2013; Lin & Chen, 2017), the participants were exposed to several decision
scenarios. In a study by Wu and Gaytán (2013), the participants were only shown the product price and seller reviews. However, also the same picture of the smartphone and the vacation package was added to each scenario to create realistic decision scenarios, which is supported by Lin and Chen (2017).
would differ between these products, this indicates that the generalizability of the results might be limited.
Independent variable - Qualitative review valence
Qualitative review valence was expressed by means of negative, neutral and positive reviews. To determine whether a qualitative review was negative, neutral or positive, the review classification of a study by Book et al. (2016) was used. In their study they determined
whether a written statement was negative, neutral or positive by conducting a pretest in which subjects rated the favorability of the reviews. The subjects were shown positive, negative and neutral reviews and had to rate the favorability on a scale from 1 (extremely unfavorable) to 7 (extremely favorable). Positive reviews were rated a 5 or higher, negative reviews a 3 or lower and neutral reviews around 4. The results of this test showed that positive reviews only contained positive statements, negative reviews only negative statements and neutral a mix of both positive and negative statements. To make sure that the hypothetical reviews used in this study were also perceived as positive, negative and neutral, we used the same construct. So, positive reviews contained only positive statements about the product, which were obtained from real reviews on the websites of Dutch retailers and travel agencies. The same goes for negative reviews, containing only negative statements, and neutral reviews, containing a mix of both positive and negative statements. So it looked like these reviews came from an actual customer, which made these scenarios even more realistic. An overview of these reviews can be found in Appendix C, where the questionnaire is displayed.
Dependent variable - Willingness to pay
(Wu & Gaytán, 2013). Therefore, the direct questioning method was also used for this study to measure the willingness to pay. So after showing the product information, respondents were asked to determine what they were willing to pay and to write down that maximum amount in euros.
Moderator - Price anchoring
The price anchors that were used for this study were obtained from different online reviews for smartphones and vacation packages that were placed on the website of Dutch retailers and travel agencies. The price anchor for a positive review was 'cheap', for a negative review 'expensive' and for a neutral review 'price is okay'. These words are commonly used on a semantic scale that ranges from cheap to expensive (Malhotra, 2010). Based on reviews on the websites of Dutch retailers, we can also argue that 'cheap' is positively valenced,
'expensive' is negatively valenced and 'price is okay' is somewhere in the middle (neutral) of these valences. As mentioned before, these words were included in the different reviews. To the best of our knowledge, using price related words as anchors in the content of a review hasn't been done before, but our way of measuring the effect of price anchoring is based on previous research.
The stimuli in a study by Book et al. (2016) consisted of photos, pricing information and customer reviews. To examine the price anchoring effect a base price was established (Book et al., 2016), this was done by showing a picture and short description of the product (brand logos were removed) and mention the selling price, which was based on real selling prices obtained from Dutch retailers and travel agencies. In contrary to the study by Book et al. (2016) each participant was exposed to every question, so control questions were needed to measure whether there is a price anchoring effect (Simonson & Drolet, 2004). Book et al. (2016) used a base resort as the 'standard' situation and a target resort that included
anchors. The overall valence in each condition was kept the same by using the same extent of positive, negative and mixed (neutral) expressions. This is supported by previous research that found that the overall review valence is more important than the content (Noone & McGuire, 2013).
Age, online shopping experience & product knowledge
Respondents indicated their age, online shopping experience and knowledge of smartphones and vacation packages in the survey. These variables were included as control variables, as they could affect the main effects in this study.
The respondents were asked to state their age, leading to interval data. As discussed, online shopping experience has shown its influence in previous studies (e.g. Zhu & Zhang, 2010). Therefore, we also controlled for online shopping experience in this study. Online shopping experience refers to the level of experience that consumers have in terms of online browsing or shopping. The scale to measure this control variable was adopted from a study by Chu, Roh & Park (2015), a nine-point likert scale was used. Also, product knowledge possibly influences the willingness to pay and was added as control variable. Since measures of objective and subjective knowledge are highly related according to some studies and to keep the questionnaire compact, we only measured the subjective knowledge in this study (e.g. Rao & Monroe, 1988). We adopted the measurement from a study by Cowley and Mitchell (2003). Participants were asked about their knowledge of smartphones and vacation packages and rated themselves on a nine-point scale that ranged from "not very
knowledgeable" to "very knowledgeable".
Analytic approach
The data was analyzed by using SPSS. First the descriptive statistics were calculated. Then, a repeated measures ANOVA, also referred to as a within-subjects ANOVA, was conducted to compare the effect of negative, neutral and positive reviews for the smartphone and vacation package. The repeated measures ANOVA may be thought of as an extension of the
Mauchly's test was conducted to determine whether there was a significant difference between the variance of the differences, the assumption of sphericity would be violated if there are significant differences. If the assumption of sphericity is violated this means that the F-ratios are not reliable, so the degrees of freedom need to be adjusted to make the F-ratio more accurate. This is done by the Greenhouse-Geisser and Huynh-Feldt correction. When ε < 0.75 the Greenhouse-Geisser correction is used and when ε > 0.75 the Huynh-Feldt
correction is used (Field, 2013). A repeated measures ANCOVA was conducted to control for the influence of age, online shopping experience and product knowledge. These variables were mean-centered, because adding a covariate does change the main effect compared to the main effect as a result of a simple repeated measures ANOVA (Thomas et al., 2009). Adding a covariate should not change the main effects of within-subject factors, so by mean centering the covariate the change in the main effect will be eliminated. However, the interaction and main effect of the covariates remain the same (Thomas et al., 2009). To determine if there was a moderating effect of price anchoring, a two-way repeated measures ANOVA was conducted. A paired-samples t-test was conducted to obtain more information about this effect (Malhotra, 2010). The results for smartphone and vacation package reviews were analyzed separately, as mentioned earlier.
RESULTS
Descriptives
Frequency Minimum Maximum Mean Standard deviation Male 49 Female 55 Age 16 63 31 12.98 Smartphone knowledge 2 9 6.64 1.69 Vacation knowledge 1 9 6.44 1.82 Online shopping experience 1 9 7.44 1.53
Table 1. Overview of descriptives
Qualitative review valence and willingness to pay
A repeated measures ANOVA was conducted to examine the relationship between qualitative review valence and willingness to pay. First the mean willingness to pay (in euros) for each review was calculated. These means indicated that a positive review resulted in a higher willingness to pay and a negative review resulted in a lower willingness to pay. An overview of these means can be found in table 2.
Review valence Smartphone Vacation
Positive € 452.92 (SD= 116.43) € 582.88 (SD= 104.03) Neutral € 360.72 (SD= 135.22) € 458.07 (SD= 129.47) Negative € 244.29 (SD= 137.31) € 216.35 (SD= 171.52)
Table 2. Overview of the willingness to pay per review type and product
= 0.92). The repeated measures ANOVA with a Huynh-Feldt correction showed us that the mean willingness to pay differed significantly between the different smartphone reviews (F(1.83, 188.72)= 162.62, p < 0.05). In case of the vacation package reviews, the mean willingness to pay also differed significantly between the different vacation reviews (F(1.71, 175.57)= 294.81, p < 0.05).
Post hoc tests were conducted, by using the Bonferroni correction. An overview of these results for the smartphone and vacation is given in table 3. There was a significant difference between a positive and neutral, positive and negative and neutral and negative review for both the smartphone and vacation (p < 0.05).
Difference (I - J) Smartphone Vacation
Positive - Neutral € 92.20 (SD= 11.36) € 124.82 (SD= 11.68) Positive - Negative € 208.64 (SD= 13.25) € 366.54 (SD= 17.56) Neutral - Negative € 116.43 (SD= 9.94) € 241.72 (SD= 16.19)
Table 3. Overview of the mean differences between the reviews
The table shows us, for example, that consumers are willing to pay €92.20 more when they buy a smartphone based on a positive review compared to the situation in which they read a neutral review. Consumers are willing to pay €116.43 less when they based their decision on a negative review compared to a situation in which they read a neutral review. So, a higher qualitative review valence (positive) leads to a higher willingness to pay. We reject the null hypothesis that there is no relationship between qualitative review valence and willingness to pay, as qualitative review valence is positively related to willingness to pay.
Main effect - Age, online shopping experience & product knowledge
we controlled for age, online shopping experience and product knowledge in case of the vacation package reviews. Also for the vacation package reviews, the mean willingness to pay differed significantly between the positive, neutral and negative vacation package reviews (F(1.81, 180.77)= 315.80, p < 0.05). We were only interested in the main effects of review valence, the complete results can be found in appendix A.
The effect of price anchoring
A two-way repeated measures ANOVA was conducted to determine whether price anchoring moderates the relationship between qualitative review valence and willingness to pay. First the mean willingness to pay (in euros) for each review with price anchor was calculated. An overview of these means can be found in table 4.
Review valence Smartphone Vacation
Positive, no anchor € 452.92 (SD= 116.43) € 582.88 (SD= 104.03) Positive, with anchor € 444.89 (SD= 106,40) € 577.40 (SD= 100.06) Neutral, no anchor € 360.72 (SD= 135.22) € 458.07 (SD= 129.47) Neutral, with anchor € 389.62 (SD= 118,34) € 455.23 (SD= 109.62) Negative, no anchor € 244.29 (SD= 137.31) € 216.35 (SD= 171.52) Negative, with anchor € 229.63 (SD= 141,37) € 245.88 (SD= 175.09)
Table 4. Overview of the willingness to pay per review type and product with price anchors
The two-way repeated measures ANOVA with a Huynh-Feldt correction showed us that there is a significant interaction effect between review type (review versus review with anchor) and review valence for smartphone reviews (F(1.86, 191.04)= 7.86, p < 0.05). However, for vacation reviews there is no significant interaction effect between review type and review valence (F(1.78, 183.05)= 2.99, p = 0.06). So, the second hypothesis is accepted for smartphone reviews and rejected for vacation reviews. This means that price anchoring moderates the positive relationship between qualitative review valence and willingness to pay for smartphone reviews. However, there is no significant moderating effect of price
Figure 1. Overview of the anchoring effect for smartphone reviews
As there is a significant interaction effect for smartphone reviews, this effect was examined further to gain more information about this effect. A paired-samples t-test was conducted to examine the effect of price anchoring on each condition in one analysis (Malhotra, 2010). The results can be found in appendix B. The results indicated that price anchoring positively strengthens the effect of neutral reviews on willingness to pay, for smartphone reviews. This means that consumers were willing to pay €28,89 more, on average, after reading a neutral review with price anchor compared to a neutral review without price anchor (p < 0.01). This increase in willingness to pay can vary between €8.32 and €49.16 on a confidence interval of 95%. There was no significant effect of price
anchoring for positive (p= 0.23) and negative smartphone reviews (p= 0.10).
DISCUSSION AND CONCLUSIONS
Summary of results
This study has tried to extent the literature on online customer reviews, by examining the effect of qualitative review valence on willingness to pay and the moderating effect of price anchoring. The conceptual model consisted of two hypotheses, which were tested by using a within-subjects design. Two products were used in this study, a smartphone and vacation package, for which the results were analyzed separately. An overview of the results can be found in table 5. As discussed in the results section, the first hypothesis was accepted for both the smartphone and vacation package reviews. However, the second hypothesis was only accepted for the smartphone reviews and in specific for neutral smartphone reviews.
Qualitative review valence and willingness to pay
Considering the theoretical background, we expected that qualitative review valence would positively influence the willingness to pay. The results support this expectation, as qualitative review valence positively influenced the willingness to pay for both the smartphone and vacation package reviews. This is in line with the results of a research by Kostyra et al. (2016), as they found that the willingness to pay increases when the score of an eBook reader review increases. The finding by Chevalier and Mayzlin (2006) that negative reviews have a negative effect on sales and positive reviews are positively related to sales, is also supported by the findings in our study. Also, prior research has shown that negative reviews lead to a negative attitude toward a product (Tang et al., 2014). Negative information seems to have more influence than positive information in decision making (Book et al., 2016). These findings are supported by this research, as the mean difference in willingness to pay seems to be larger for neutral and negative reviews than for neutral and positive reviews.
Price anchoring
Another expectation, based on the theoretical background, was that price anchoring would strengthen the positive relationship between qualitative review valence and willingness to pay. However, the moderation effect of price anchoring was only partly supported by the findings in this study. The anchoring effect for negative and positive reviews was
insignificant. These results are contrary to the results found in a study by Wu and Cheng (2011), as they found that a high anchoring value leads to a higher willingness to pay. In a study by Book et al. (2016), the anchoring effect only occured in positive review situations and their results didn't show a significant effect for negative reviews. Their study found that negative reviews are more important than specific price information, which is supported by the findings of our study. Our study used other anchors than previous studies, so these
consumers are only influenced by the anchoring effect of incidental numbers when they have a weak internal reference price.
We found an anchoring effect for neutral smartphone reviews, but not for neutral vacation package reviews. A possible explanation for this could be that the type of product affects the way consumers are influenced by the price anchors. For example, Kuijken et al. (2017) found an anchoring effect for radically innovative products and not for incrementally innovative products. In this study, the smartphone was chosen as search product and the vacation package as experience product. As discussed earlier, price anchors in the content of a review can reduce uncertainty regarding the reference price as these anchors give the customer direct information (Simonsohn, 2009; Wu et al., 2013). Jiménez and Mendoza (2013) found that the credibility of a review is affected by the level of detail in case of search products and reviewer agreement in case of experience products. So, the level of detail is more important for search products and adding price anchors increases the level of detail. This might explain why adding price anchors to the content of a review was only effective in case of the smartphone and not in case of the vacation package.
Managerial implications
The findings have important implications for companies that sell their products or offer their services online and permit customer reviews on their websites. Understanding the effect of customer reviews has become important for managers in a way that they could use this information to influence consumers' buying decisions. The results of this study show that qualitative review valence, so the valence of a written text, positively influences the willingness to pay. Also, the results suggest that it might be profitable to stimulate neutral reviews accompanied by neutral statements about the product price, as this could lead to a higher willingness to pay. However, caution is recommended for the latter suggestion, since the effect of neutral price anchors was only partially significant in this study.
suggests that companies may need to monitor the effect of reviews on the different product types, not just on product or category level.
Negative and positive price anchors didn't have a significant effect on negative and positive reviews. Therefore, positive and negative price related statements in the content of a review don't have consequences for the willingness to pay based on this study. This means that companies can leave these price related anchors in the content of a review or use them to summarize the content of the reviews, without causing an increased negative or positive effect on willingness to pay. This knowledge provides managers with a better understanding of the effects of qualitative reviews.
Limitations and future directions
This study has a few limitations that should be considered. The first limitation concerns the data that was used in this study. The data was collected in the Netherlands, which limits the generalizability of this research. With only 104 respondents, this sample was not
representative for the Dutch population. Also, 56% of the respondents were 20-30 years old, which makes it a relatively young sample. Therefore, a recommendation for future research is that a larger sample should be used and research should be extended to other countries, to improve the generalizability of the results.
Another limitation of this study is that only open-ended questions were used to
measure the willingness to pay and subjects made a hypothetical choice. The reason for using this method is that previous research has shown that the use of open-ended questions is a very appropriate method to measure the willingness to pay (Miller et al., 2011). Also, several other studies use this method to date (e.g. Lin & Chen, 2017). However, results might slightly differ across the different methods used for measuring willingness to pay. To verify the results, future research can examine the effects of review valence on willingness to pay by also using other methods, for example a conjoint analysis, to measure the willingness to pay.
written statement about the price was added for the review with price anchor. Future research is recommended to increase the amount of different reviews to improve the generalizability of the results.
Another limitation is that only two products were used in this study and only one type of price anchoring. There are different types of anchors that have shown mixed results in prior studies (e.g. Simonson & Drolet, 2004; Carroll et al., 2009). Especially the type of product could influence the extent to which consumers are influenced by a review (e.g. Sen & Lerman, 2007; Kuijken et al., 2017). Future research should use different types of anchors and products to examine whether the results differ across these different types. It might be interesting for future research to further explore the effects of qualitative review valence and price anchoring.
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1 | faculty of economics
and business marketing
28-08-2015 faculty of economics
and business marketing
THE DIFFERENTIAL EFFECT OF QUALITATIVE
REVIEW VALENCE ON WILLINGNESS TO PAY:
THE MODERATING EFFECT OF PRICE ANCHORING
| 16-08-2018
Master Thesis Defense
Jordi Zaoudi – S2281090
faculty of economics
and business marketing
TABLE OF CONTENTS
• INTRODUCTION
• THEORETICAL FRAMEWORK
• RESEARCH DESIGN
• RESULTS
faculty of economics
and business marketing
INTRODUCTION
How strong are the different effects of negative, neutral and
positive qualitative consumer reviews on the willingness to
pay and how does price anchoring in the content of a review
influence this effect?
Why is this interesting?
› Customer reviews have become important for both customers and
companies
(Cui et al., 2012)› Customers attach more value to text valences and use the information to
change their perceptions
(Tsang & Prendergast, 2009)› Several factors that influence the effect of online reviews on willingness to
pay can also be linked to price anchoring
(e.g. Wu et al., 2013; Furnham & Boo, 2011)faculty of economics
and business marketing
THEORETICAL FRAMEWORK
Definitions
Qualitative review valence
› Written statements of negative, neutral or positive experiences
(Jiménez & Mendoza, 2013)Willingness to pay
› Highest price that a customer wants to pay for a product
(Le Gall-Elly, 2009)Price anchoring
› Customers’ value judgement is adjusted from the initial value by a
reference point
(Tversky & Kahneman, 1974)faculty of economics
and business marketing
THEORETICAL FRAMEWORK
Conceptual model
H1:
Qualitative review valence is positively related to willingness to pay
faculty of economics
and business marketing
RESEARCH DESIGN
Survey
› Smartphone & vacation package
› Negative, neutral and positive reviews
› With or without price anchor
§
‘cheap, price is okay, expensive’
› Open-ended question
1.
Read the description and review
2.
How much are you willing to pay for this
phone/vacation?
Participants
› 104 Dutch consumers
faculty of economics
and business marketing
RESULTS
In specific:
› Price anchoring positively strengthens the effect of neutral reviews on willingness to
pay, but only for smartphone reviews
faculty of economics
and business marketing
DISCUSSION AND CONCLUSIONS
Managerial implications
› Companies may need to monitor the effect of reviews on willingness to
pay for different product types, not just on product or category level
§
Search (smartphone) vs experience (vacation) products
› Companies can leave these price related anchors in the content of a
faculty of economics
and business marketing
DISCUSSION AND CONCLUSIONS
Limitations
› Partially significant
› Dutch consumers
› Open-ended questions
› Two products and one type of price anchoring
Future directions
› Extend to other countries
faculty of economics
and business marketing
