Social Influence on Product Rating in Online Consumer Reviews
‘The effect of the message, platform and experience’
Social Influence on Product Rating in Online Consumer Reviews
‘The effect of the message, platform and experience’
Master thesis
University of Groningen, the Netherlands Faculty of Economics and Business Master of Business Administration Marketing Management
Pieter Faber Schoutstraat 10
9843 BD GRIJPSKERK, the Netherlands +31 6 15681619
p.faber1@student.rug.nl Student number: 1917706
Supervision
University of Groningen, Faculty of Economics and Business, Department of Marketing First supervisor: dr. J.A. (Liane) Voerman
MANAGEMENT SUMMARY
This study has a main focus on online consumer reviews. In particular on the post-purchase product rating, thus when consumers are likely to post an online consumer review. Investigated is if the type of platform (third party vs. company owned) and the type of message (emotional loaded vs. factual based) have an influence on the shared product/service experience of consumers. Existing literature has a large focus on the use of online consumer reviews in the pre-purchase stage of the buying process and less emphasis has been paid on the post-purchase stage.
With a survey, consisting of eight groups (two types per independent variable), product rating was being measured.
In short, this are the most important findings of the study.
A positive experienced consumer does not mind which platform he/she reads or submits reviews, the rating they will give is around the same score. Looking at negative experiences, consumers tend to publish less negative reviews on company owned platforms in comparison with third party platforms. When consumers confronted with a negative experience of a service, the degree in which they are negative is much larger in comparison with the degree of positivity when the experience is positive. Thus, the weight of a negative experience is higher than of a positive experience.
Consumers who had a positive experience, give a slightly higher product rating when they read an online consumer review from other users in comparison with a review from an expert. When consumers had a negative experience, reading a review from an expert positively influences the negative experience to become less negative.
TABLE OF CONTENT
1 Introduction ... 1
1.1 What factors play a role within OCR ... 2
1.2 Relevance ... 3 1.3 Structure ... 3 2 Literature framework ... 4 2.1 Independent variables ... 4 2.1.1 Experience ... 4 2.1.2 Platform ... 5 2.1.3 Message ... 5 2.2 Covariates ... 6 2.2.1 Credibility ... 6 2.2.2 Expertise ... 7 2.3 Conceptual model ... 8 3 Research design ... 10 3.1 Design ... 10
3.2 Procedure of the experiment ... 10
3.3 Scales ... 10 3.4 Plan of analysis ... 11 3.5 Manipulation checks ... 12 4 Results ... 14 4.1 General results ... 14 4.2 Homogeneity of slopes ... 15 4.3 Ancova ... 16 4.4 Summary... 19
5 Conclusion and Discussion ... 21
5.1 Discussion of results ... 21
5.2 Managerial implications ... 22
5.3 Limitations and future research ... 22
6 References ... 24
7 Appendix ... 28
Appendix A: Questionnaire (Dutch only)... 29
Appendix B1: ANCOVA - Homogeneity of slopes ... 32
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1 INTRODUCTION
Technological developments on IT enable consumers to broaden their scope searching for information in the pre-purchase stage of the buying process. In the online world, consumers tend to share their experiences, opinions and knowledge with others via message boards, internet forums, chat rooms and online consumer reviews. The internet also provides consumers with an easy medium for communicating and interacting with consumers and web site owners (Huang & Chen, 2006).In the past, consumers could only get information about a product from salespeople or via word-of-mouth (WOM). The only WOM sources were direct contacts like family or friends who had experience with a product/service or heard from it via their social network.
Nowadays, electronic word-of-mouth (eWOM) represents one of the most influential sources of information transfers by consumers (Khare et al, 2011). The rising importance of the internet has enabled new forms of communication that further empowers consumers for sharing information and user experiences from consumer to consumer, business to consumer and other way around. Emerge of eWOM has been changing people’s behavior because of the growth of internet usage (Dellarocas, 2003). eWOM faced an enormous growth in popularity, mainly on online communities where consumers share their evaluations of products/services to a larger audience. The increased accessibility of eWOM made consumers more often integrate it into their pre-purchase stage of the buying process (Hoyer & MacInnes, 2008; Lee et al., 2008)). The creation of online communities and social networks has made the power of electronic word-of-mouth (eWOM) grow enormously for both consumer and marketers (Yang et al, 2012). In research of Schlosser (2011), over half (58%) of consumers prefer sites with peer reviews and nearly all (98%) of the online shoppers reported reading peer review before making a purchase. Online word of mouth can also be used as a technique for viral marketing in which a company uses customers to promote a product or service to prospective customers, which is the case when companies include forums for exchanging word of mouth on their product pages (Mitchell & Khazanchi, 2010). In comparison with traditional advertising (e.g., TV, newspapers) and other marketer-controlled sources, word of mouth is perceived by consumers as being more credible than private signals and more accessible through social networks (Mitchell & Khazanchi, 2010). eWom is particularly interesting for service goods. In studies of Haygood (1989) and Klein (1998), proof is given that eWOM processes offer solutions for the intangibility of services.
2 al, 2010). Attributes making an OCR helpful to use are attribute value information, recommendation an overall evaluation (i.e. rating) and an explanation (i.e. arguments) (Lee et al, 2008; Schlosser, 2011).
What triggers consumers to participate in such online interaction? Henning-Thurau (2004) conclude that desire for social interaction, desire for economic incentives, concern for other consumers, and the potential for self-enhancement are the primary motivators of online review contribution. Consumer’s affective elements of satisfaction, pleasure, and sadness all motivated consumers to wish to share experiences with others (Jalilvand et al, 2010).
Remarkable are the result of Anderson (1998) and Lee et al. (2008) who mention that dissatisfied consumers engage in greater word of mouth than satisfied consumers. Negative communications are likely to have greater impact than positive information. Lee et al (2008) add to this finding that when the proportion of negative online consumer reviews increases, high involved consumers tend to conform to the perspective of the reviewers, depending on the quality of the negative online reviews. In contrast, low involved consumers tend to conform to the perspective of reviewers regardless of the quality of the negative online consumer reviews. In short, high involved consumers are really analyzing the content of the review, where low involved consumers only look at the message shortly and base their attitude upon.
Mudambi & Schuff (2010) found that moderate reviews are more helpful than extreme reviews (whether they are strongly positive or negative) for experience goods, but not for search goods. Further, lengthier reviews generally increase the helpfulness of the review, but this effect is greater for search goods than experience goods. Negative emotions in a negative review lower perceived reviewer rationality, thereby reducing review informative value and lead to less negative product evaluations. Results show that negative emotions in a single review decrease informative value and decrease negative impact on product evaluations. (Kim & Gupta, 2012).
1.1 WHAT FACTORS PLAY A ROLE WITHIN OCR
3 “What social influence does product experience have on a post-purchase product rating and what is the moderating effect of the type of platform and type of message?”
This problem statement shows a lot of variables which can have an influence on the overall product rating of consumers. To cope with a better vision on what subjects the study is about, the problem statement is split into several research questions:
1. What is the role of product experience on post-purchase product rating?
2. What is the moderating role of the type of message on product experience’s effect on post-purchase product rating?
3. What is the moderating role of the type of platform on product experience’s effect on post-purchase product rating?
1.2 RELEVANCE
This topic is has relevance for practitioners in online marketing, who focus on the online word of mouth. Binding consumers to a product via the online channels is proven to be harder than via the offline channels. The online environment enables consumers to influence a larger group of
consumers with their word of mouth. To have better control of this, marketers should have knowledge of how a message is influencing their customers and how platforms influence the behavior of consumers.
This topic also has relevance for in the current literature about eWOM. Several studies have paid attention to online consumer reviews. All focus on OCR’s in the pre-purchase stage of purchasing of a product. For instance, Zhu et al. (2010) found that people’s online purchase decisions are influenced by OCR’s from others.
There is little research done about the effects of other consumers’ online reviews on the actual product rating. Sridhar & Srinivasan (2012) aim at already existing OCR’s and their effect on product recovery after failure, Schlosser (2005) reports that consumers decrease their own OCR after reading OCR’s from others. They do not mention the factors underlying that effect, what the aim is of this study. Senecal and Nantel (2004) provide a recommendation that examining the factors of social influence (e.g. platform and message) might be interesting for future research of their work.
1.3 STRUCTURE
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2 LITERATURE FRAMEWORK
In this section the linkage system between the variables and covariates will be analyzed. There is central relation between experience (independent variable) and product rating (dependent variable). On this central relation, platform (independent variable) and message (independent variable) is suggested to have influence. Furthermore, it is expected that expertise (covariate) and credibility (covariate) should have influence on the independent variables platform and message.
2.1 INDEPENDENT VARIABLES
2.1.1 EXPERIENCE
Consumers might have past experiences with a similar product or brand which can have a negative influence on using OCR’s. Consumers have different information processing capabilities in inferring benefits from online consumer reviews due to different levels of consumer experience. (Chen & Xie, 2008).
Richins and Root-Shaffer (1988) see that when consumers have more experience with a product, they tend to use only reviews which contain information about the product. The construct of experience could also be pointed out with a focus on the Elaboration Likelihood Model of Petty and Cacioppo (1986) as Park and Kim do in their 2008 research. Consumers with low product/service experience are more likely to focus on peripheral cues like the number of arguments, while consumers with a higher level of experience are more engaged through the central route and aim for argument quality.
A negative experience is often used to complain about a service or product. The literature of complaining suggests that consumers with a negative experience, with a certain product or service, could experience reduced dissatisfaction by venting their frustrations (Alicke et al., 1992; Bennett, 1997; Nyer, 2000). Although complaining behavior benefits marketers by providing them with useful information, negative WOM hurts marketers because of its ability to taint the opinions of numerous potential customers (Richins, 1983).
Consumers with negative experiences are likely to feel a lower threshold to engage in posting their reviews than consumers with positive experiences (Anderson, 1998). People expect a product or service to serve them properly, doing what they ought to do and therefore feel less initiated to share their opinions. Hoyer and MacInnes (2008) found that negative experiences are more often communicated to more people and given greater weight in decision making in comparison with positive experiences. Consumer place greater weight on negative experiences of others during decision making (Huang & Chen, 2006). Anderson (1998) also implies that negative reviews have greater influence on consumers’ willingness to buy than positive reviews. However, negative experiences might also have a similar effect on post-purchase product rating. Therefore, the following hypothesis is formulated:
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2.1.2 PLATFORM
Anyone who reads or wants to post an OCR is confronted with a choice of platform. Dou et al. (2012) suggest there are two types of platforms to use; company owned platforms and third party platforms. When consumers want to post a review on an online review platform, they have the choice between two alternatives to post it on; company owned platforms or third party platforms (e.g. kieskeurig.nl, epinions.com).
Company owned review platforms are 100% in control of the company. So, as visitor or consumer, you are not sure if the reviews posted on the platform are real or that the most negative reviews are left out. According to Mitchell and Khazanchi (2010) companies mostly exclude negative reviews related to customer service issues, price differences with competing products and other comments which are not related to the actual product. The reviews they allow on their review platform tend to focus on product attribute information as performance, features and reliability because they are easier to measure. As a result, these platforms can look saturated with the same kind of reviews. Different from company owned platforms, third party review platform are seen as independent. OCR’s are based on personal experiences, which can be highly affected by the reviewer’s preferences as well as their situation of use. For this reason, Chen and Xie (2008) state that third party platforms are more likely to focus on how a product matches specific individual preference and usage conditions. Third-party product reviews usually provide product information (e.g., basic features/functions and prices) based on user experience or expert evaluation using one of several different review formats. Many third party reviewers adopt a description format to provide detailed attribute facts about a product without making overall recommendations to its competing products (Yubo & Jinhong, 2005). Other reviewers adopt a recommendation format that not only provides descriptive product attribute information but also selects winners to recommend to consumers based on overall product performance and prices. Objectivity is the key word for third party platforms. Research of Chen & Xie (2008), Zhanga et al. (2010) and De Maeyer & Estelami (2011) show that third party platforms are seen as more reliable than company owned platforms, and are more frequently used as input for purchase decisions by consumers. These insights provide a base to define the hypothesis:
H2: ‘Third party platforms have a positive moderating influence on the effect of product experience on product rating in comparison with company owned platforms’
2.1.3 MESSAGE
Anyone who publishes an online consumer review can be seen as an opinion leader for others who consider purchasing a product. Opinion leaders have influence because they generally have no personal stake in whether their opinions are heeded, so their opinions are perceived as unbiased and credible (Hoyer & MacInnes, 2008). They are not necessarily well-known people; they may be friends, family, celebrities or professionals.
6 expectations of others whereas informative influence is seen as influence to accept information obtained from another as evidence for reality”. Normative influence is enhanced when groups, to whom consumers are committed to, are cohesive. Informational influence is greater when groups are less cohesive and the influencer is seen as more expert than members of the group are (Hoyer & MacInnes, 2008).
Another theory that could be applied to message influence of online consumer reviews is the Elaboration Likelihood Model (ELM) from Petty and Cacioppo (1986), wherein they make a distinction between central route and peripheral route processing of information. Central route persuasion aims for the arguments (i.e. text), whereas the peripheral route puts more emphasis on heuristics (i.e. emotion).
When applying these theories to online consumer reviews, we can make a distinction between factual influence and emotional influence. Factual exert social influence from the central route of persuasion, aiming on the functional aspects of the products. Factual also implies an informative way of social influence. Emotional uses a more peripheral route of persuasion with a focus on experience and emotional aspects of the product. They base their reviews on experience of a product which they are the real users of, and follow a normative source of social influence.
Online reviews strongly influence consumer product choices. Flanagin and Metzger (2013) make a clear distinction in review; user generated and expert generated reviews. In a study of Huang and Chen (2006), it can be said that reviews from users were more influential than those of an expert. Consumers tend to rely more on recommendations from user like themselves than from an expert who just ‘tests’ a product or service and not really experiences it like a user does. Users tend to describe product experiences with emotional aspects, whereas experts need to be objective and describe the more factual aspects of a product. Another fact about the source of an online consumer review is that consumers are influenced more by collective intelligence than by a small group of experts. Because people are curious about the likes of others, the emotion based reviews have become a trusted and popular information source. Emotional information is considered a more trustworthy source than only factual information because the actual experience is missing. From this theoretic background, the following hypothesis is formulated:
H3: Emotional aspects of an online consumer review have a positive moderating influence on the effect of product experience on product rating in comparison with factual aspects
2.2 COVARIATES
2.2.1 CREDIBILITY
7 Bickart and Schindler (2001) indicate that OCR’s have greater credibility in inducing empathy than advertising. Messages on these sources exert a more powerful influence on consumer attitudes than marketer-generated information (Chiou & Cheng, 2003).
The credibility of an OCR is affected positively if claims are relevant, objective, and verifiable (Racherla et al, 2012; Kempf & Palan, 2005; Dillard & Shen, 2005). The manner in which the reviewer argues for or against the product increases the credibility and trust perceptions (Racherla et al., 2012). An OCR is essentially an argument made by a reviewer to either encourage or dissuade consumers from buying a particular product or service (Racherla et al, 2012).
Another factor which improves the credibility of the OCR has to do with the social influence people have on each other. An individual may reduce uncertainty by choosing to communicate with other people who share similar values and social identity. Knowing the identity of the information source helps individuals find people who have much in common with themselves (Kusumasondjaja et al, 2012).
A research of (Kusumasondjaja et al, 2012) indicates that a negative online review is deemed more credible than a positive online review, while a positive online review leads to a greater initial trust than a negative review.
Another driver of credibility is argument quality. Argument quality is a significant driver of trust even in online reviews. In using argument quality, we build upon some of the deficiencies in previous studies that typically used either the review valence (positive or negative) (Ba and Pavlou, 2002) or review length (number of words).
These insights give enough evidence to make the assumption that credibility would have a positive influence on both the type of message and type of platform in inducing consumers writing their OCR’s. This leads to the following hypotheses:
H2a: A type platform being more credible positively influences the moderating effect of either third party or company owned platforms
H3a: A type message being more credible, positively influences the moderating effect of either factual or emotional type of messages
2.2.2 EXPERTISE
Every consumer has a different level of knowledge or prior experiences with a product or service. When you for example have little experience with a product group, you are more triggered to find attribute information in forms of other consumers’ experiences.
8 According to Elaboration Likelihood Model, consumers with low expertise are more likely to focus on a peripheral cue such as the number of arguments, while consumers with high expertise are more likely to engage in effortful cognitive activity through the central route, and they focus on the argument quality (Petty et al., 1983). Individuals with different levels of consumer expertise seek different types of information. More experienced users prefer specific attribute data, while novices seek data that are interpreted and reproduced to be easily understandable (Park & Kim, 2008). According to a study of Mason et al (2001), positive previous product experience increases product attribute ratings. But it negatively affects the influence of consumer ratings. Consumers with a high degree of experience are less affected by the type of platform nor type of message (Flanagin and Metzger, 2013). These key insights allow that the following hypotheses can be formulated:
H2b: ‘Consumers with a high level of expertise have a negative influence on the moderating effect of either factual or emotional type of messages’
H3b: ‘Consumers with a high level of expertise have a negative influence on the moderating effect of either third party or company owned platforms’
2.3 CONCEPTUAL MODEL
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Figure 1 Conceptual model
Complementary to the figure above, here follows a short overview of the hypotheses. Hypothesis
H1 Negatively experienced consumers have negative impact on the product rating in comparison with positive experienced consumers
H2 Third party platforms have a positive moderating influence on the effect of product experience on product rating in comparison with company owned platforms
H2a A type of platform being more credible positively influences the moderating effect of either third party or company owned platforms
H2b Consumers with high expertise have a negative influence on the moderating effect of either third party or company owned platforms
H3 Emotional aspects of an online consumer review have a positive moderating influence on the effect of product experience on product rating in comparison with factual aspects
H3a A type of message being more credible positively influences the moderating effect of either factual or emotional type of messages
H3b Consumers with high expertise have a negative influence on the moderating effect of either factual or emotional type of messages
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3 RESEARCH DESIGN
In this chapter, the methods used to get answers to the hypotheses will be discussed. First the design of the experiment will be build, followed by the procedure. How the covariates are being measures is stated in the scales section. In the sample the characteristics of the participants is being discussed, followed by the plan of analysis for the result chapter.
3.1 DESIGN
To find answers for the research question, the study requires an experiment 2(positive vs. negative experience) x2 (third party vs. company owned platform) x2 (emotional vs. factual type of message) design. As seen in table 1, the experiment has eight groups; third-positive, emotional-third-negative, emotional-company-positive, emotional-company-negative, factual-third-positive, factual-third-negative, factual-company-positive and factual-company-negative.
The experiment is conducted by a questionnaire for each of the eight groups. The questionnaire contains a general part and an in-depth part. The in-depth part consists of a positive or a negative experience and a review of another source.
Table 1 Overview of the experimental design
Type of platform Product experience Type of message
Emotional Factual
Third party Positive experience X1 X2
Negative experience X3 X4
Company owned Positive experience X5 X6
3.2 PROCEDURE OF THE EXPERIMENT
The design consists of 8 different questionnaires to execute. In order to get representative results, the minimum amount of participants is set at 200+. The participants need to be divided over the 8 groups equally.
Introduce the questionnaire to the respondents and tell them briefly what the purpose of the research is without telling which group they are signed in to. After the respondents have finished filling in their questionnaire, ask if they have comments about the questionnaire.
3.3 SCALES
Operationalization is needed to make product rating (dependent variable), covariates (message credibility and platform credibility) measurable. Also a manipulation check which checks if the manipulation of message is done correctly needs to be operationalized. Table 2 gives an overview of how variables are measured.
Table 2 Codebook for analysis
Concept Source Items Internal
consistency (α) Product rating Zoover.nl A 10 point grading like the academic grading in
the Netherlands (1 ‘very poor’ to 10’ excellent’)
11 type of message and
Metzger, 2000
’to 5 ‘totally agree’) on five factors: Believability Accuracy Trustworthiness Bias Completeness Credibility of the type of platform Flanagin and Metzger, 2000
A 5-point likert scale (range 1 ‘not agree at all ’to 5 ‘totally agree’) on five factors:
Believability Accuracy Trustworthiness Bias Completeness 0,862 Consumer expertise Mitchell and Dacin, 1996
A 5 point likert scale (range 1 ‘helemaal mee oneens’ to 5 ‘helemaal mee eens’) on three factors
Experience with renting holiday homes on campsites
Experience with renting holiday homes in general
Experience compared with the average person
0,915
Difference
emotional/factual
A 5 point likert scale (range 1’helemaal mee oneens’ to 5 ‘helemaal mee eens’ on four factors
Consumer expertise of reviewer Objectivity
Emotional Factual
0,786
3.4 PLAN OF ANALYSIS
After processing the date in SPSS, the analytic test below are conducted to see Internal consistency of scales
Internal consistency is used to evaluate the reliability of a summated scale where several items are summed to form a total score. The measure involved in measuring is Cronbach’s alpha. This coefficient varies between 0 and 1, and a value of 0,6 or less generally indicates internal consistency and variables cannot be summed up (Malhotra, 2010). In this study there are four variable s which need a Cronbach’s alpha as consistency measure; credibility of platform, credibility of message, expertise and difference between emotional and factual message. Results can be found in table 2 in section 3.3.
Manipulation test
12 the manipulations significantly differ, a sample t-test is executed (two experimental groups per manipulated variable) with a p-value of 0.05. Results of this test can be found in section 3.5.
Hypothesis test
In order to gain results concerning the hypotheses, an ANCOVA test is performed. An ANCOVA test is most suitable measuring the impact of the covariates credibility and consumer expertise on the independent variables experience, type of platform and type of message. Executing an ANCOVA concern three steps before making conclusions:
1. The homogeneity of slopes has to be tested to see if covariates have significant influence on the independent variables. Poremba and Rowell (1997) assert that the homogeneity of slopes assumption is often neglected and that this is where most researchers fail in terms of obtaining accurate ANCOVA analyses. The test concerns the following relations:
The effect of credibility on the moderating role of the type of message; The effect of credibility on the moderating role of the type of platform; The effect of expertise on the moderating role of the type of message; The effect of expertise on the moderating role of the type of platform.
Once these tests show no significant measures, the ANCOVA can be carried out to test the hypotheses. If the homogeneity of slopes shows significant measures, the ANCOVA is less suitable for this situation and a regression is more appropriate.
2. Assuming the results of the homogeneity of slopes are not significant, the actual ANCOVA can be performed. Product rating is inserted as dependent variable, experience, message and platform are imported as fixed factor (independent variables) and expertise and credibility are inserted as covariates. The results of the ANCOVA are the answers to the hypotheses. 3. Last step is an overview of estimated marginal means which present a virtual presentation of
the results from where main conclusions can be drawn.
3.5 MANIPULATION CHECKS
Manipulation checks ensure the research being reliable and significant on the variables being measured. The manipulated variables are experience, type of message and type of platform. In the tables below, each of the manipulations is checked using an independent sample T-test to prove if the manipulations are significant or not.
Analyzing the outcome of the manipulation of experience (table 3), the conclusion can be made that experience gives significant differences on product rating with a p-value of 0.000. So a consumer with a positive experience significantly gives a different product rating than a consumer who had a negative experience.
Table 3 Results independent sample t-test of results
Experience N Mean SD Sig.
Positive 101 7.99 0.92 0.000
13 Table 4 provides the manipulation test results for the type of message. A p-value of 0.537 shows that there is no significant difference among factual and emotional type of messages. The conclusion of this test is that the two types of messages (factual and emotional) do not significantly differ from each other when it comes to a product rating.
Table 4 Results independent sample t-test of message
Type of Message N Mean SD Sig.
Emotional 98 6.06 2.32 0.537
Factual 103 5.86 2.22
The manipulation check of the independent variable platform gave to following insight. With a p-value of 0.354 it can be concluded that the product rating respondents gave to a review from a third party platform did not significantly differ from the product rating from a company owned platform.
Table 5 Results independent sample t-test of platform
Platform N Mean SD Sig.
Third party 96 6.11 2.33 0.534
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4 RESULTS
This chapter contains the main results of the research. First some general results of the sample are displayed. Second, an analysis of the homogeneity of slopes will be given to find out if the ANCOVA test is allowed to be performed. Third, the analysis of the hypotheses will lead towards conclusions.
4.1 GENERAL RESULTS
The goal of the survey was to obtain input of at least 200 respondents, which implies that each experimental group contains at least 25 respondents (8x25). The final sample consists of 201 respondents, so this criterion is met. General results can be found in the tables 6 till 8
From the 201 respondents, 112 (55.7%) are men and 89 are women (44.3%) with ages between 18 and 64. The average age is determined to be 34.46 years.
More topics related are to have a look at the average product rating per group. On average, respondents rate their experience with a 5.96 on a 10 point scale. The highest product rating (8.56) is given by the group confronted with a positive experience, an emotional message and found on a third party platform. The lowest average rating (3.69) is given by the group containing a negative message, an emotional message and found on a third party platform.
Table 6 Gender distribution
Gender Frequency Percent
Men 112 55.7
Women 89 44.3
Table 7 Age distribution
Age
Mean Median Minimum Maximum
34.36 30 18 64
Table 8 General results of the variable product rating
Independent variables N Mean product
rating
Experience Platform Message
Positive Third party Emotional 25 8.56
Factual 25 7.80
Company owned Emotional 26 7.69
Factual 25 7.92
Negative Third party Emotional 23 3.69
Factual 23 4.04
Company owned Emotional 24 3.95
Factual 30 3.93
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4.2 HOMOGENEITY OF SLOPES
The homogeneity of slopes test is being executed to determine if an ANCOVA test is appropriate to use. The homogeneity of slopes determines whether an ANCOVA test is appropriate to use without any interfering interactions among independent variables and covariates. Lack of testing homogeneity of slopes or neglecting the significance might lead to type II errors (Poremba & Rowell, 1997).
There are 4 interactions which have to be tested on homogeneity of slopes;
The effect of credibility (CV) on the moderating role of the type of message (IV); The effect of credibility (CV) on the moderating role of the type of platform (IV); The effect of expertise (CV) on the moderating role of the type of message(IV); The effect of expertise (CV) on the moderating role of the type of platform (IV). Once the results of these test are non-significant (p>0.05), an ANCOVA is suitable to test the hypotheses. In appendix B1 the SPSS output of the homogeneity of slopes test can be found. From the results, from which a short summary can be seen in table 9, the main conclusion is that none of the covariates (credibility and expertise) significantly interacts with the independent variables (message and platform). Message (IV) and credibility (CV) show no significant interaction with a p-value of 0.087 which is larger than 0.05. The same counts for credibility and platform (0.217), expertise and message (0.251) and expertise and platform (0.709).
Concluding, an ANCOVA test is allowed to use because there are no interfering interactions between the covariates and independent variables.
Table 9 Overview of the homogeneity of slopes test
Variables (CV * IV) F Sig.
Credibility * Message 2.955 0.087
Credibility * Platform 1.537 0.217
Expertise * Message 1.326 0.251
Expertise * Platform 0.140 0.709
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4.3 ANCOVA
Given the results of the homogeneity of slopes provide enough evidence to conclude that there are no interaction effects among covariates and independent variables, an ANCOVA test will be applied to find answers to the hypotheses.
Table 10 Output ANCOVA test
Source F B Sig. Credibility_Platform 1.269 -0.421 0.261 Credbility_Message 6.309 0.976 0.013 Expertise 3.814 -0.148 0.052 Experience 590.567 3.614 0.000 Platform 2.005 -0.199 0.158 Message 0.001 0.070 0.981 Experience * Platform 3.192 -0.207 0.076 Experience * Message 2.555 -0.234 0.111
*Dependent variable = Product rating Experience
‘Negatively experienced consumers have negative impact on the product rating in comparison with positive experienced consumers’
A visual picture of the results (figure 2) gives an indication that a positive experience leads to a doubled score on product rating in comparison with a negative experience. The mean product rating consumers give for a negative experience (M= 3.91) is much lower than the mean product rating consumers give for a positive experience (M= 7.99).
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Figure 2 Estimated marginal means of product rating (DV) influenced by experience (IV)
Platform
‘Third party platforms have a positive influence on the effect of product experience on product rating in comparison with company owned platforms’
Figure 3 gives a graphical impression of the results which show that a company owned platform leads towards a slightly higher product rating. The results show the means of positive experience with OCR’s on a third party platform (M= 7.78), a negative experience with OCR’s on a company owned platform (M= 3.84), a positive experience with OCR’s on a company owned platform (M= 7.82) and a negative experience with OCR’s on a company owned platform (M= 4.32) already indicate for rejection of the hypothesis. The significance test of the ANCOVA, table 9, complements the results (p= 0.076), so the h2 is not supported.
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Figure 3 Estimated marginal means of product rating (DV) influenced by experience (IV) and moderated by platform (IV)
Message
‘Emotional aspects of an online consumer review have a positive influence on the effect of product experience on product rating in comparison with factual aspects’
19 Credibility
H2a and H3a concern hypotheses with the covariate credibility. H2a expects that when a platform is seen as more credible than the other, this would have a positive influence on the moderating effect of either third party or company owned platforms. In case of H3a it is expected that when a message is seen as more credible than the other, it has a positive influence on the moderating effect of either factual or emotional type of message’.
As already tested in chapter 4.2, the covariate credibility has not been tested as significant (p= 0.087 for message and p= 0.217). Therefore, hypotheses h2a and h3a are not supported. Credibility appears to not have a positive moderating role on the independent variables platform and message. Expertise
Expertise is tested in H2b and H3b. H2b assumes that consumers with high expertise have a negative influence on the moderating effect of either factual or emotional type of messages and h3b gives the assumption that consumers with high expertise have a negative influence on the moderating effect of either third party or company owned platforms.
The results of the homogeneity of slopes test (chapter 4.2) already gave the conclusion that expertise does not have a significant effect (p= 0.251 for message and p= 0.709 for platform). So, hypotheses 2b and 3b are not supported by the results. Expertise does not have a negative correlation with the independent variables message and platform.
4.4 SUMMARY
In short, these are the most important findings:
Hypothesis Outcome
20 product rating in comparison with positive experienced consumers
H2 Third party platforms have a positive moderating influence on the effect of product experience on product rating in comparison with company owned platforms
Not supported
H2a A type of platform being more credible positively influences the moderating effect of either third party or company owned platforms
Not supported H2b Consumers with high expertise have a negative influence on the
moderating effect of either third party or company owned platforms
Not supported H3 Emotional aspects of an online consumer review have a positive
moderating influence on the effect of product experience on product rating in comparison with factual aspects
Not supported
H3a A type of message being more credible positively influences the moderating effect of either factual or emotional type of messages
Not supported H3b Consumers with high expertise have a negative influence on the
moderating effect of either factual or emotional type of messages
Not supported
First, evidence is found about the role which the type of message has in influencing consumers in adding their own online consumer review. We found that consumers who have had a positive experience with a service are providing a higher rating when they are confronted with reviews based on emotional experiences. When looking at the negative experiences of consumers, a higher rating was provided with the presence of reviews based on facts.
Second, we find proof that the type of platform exerts social influence. A positive experienced consumer does not mind which platform he/she reads or submits reviews, the rating they will give is around the same score. Looking at negative experiences, consumers tend to publish more positive reviews on company owned platforms in comparison with third party platforms.
21
5 CONCLUSION AND DISCUSSION
Consumers exert a strong influence of online consumer reviews when deciding to buy a certain product or service. Not only the decision process is influenced, also the rating process itself is being influenced. In this article, we develop theory and report evidence on how social influence has an impact on consumers’ rating behavior. In this chapter we conclude with relevant contributions to marketing theory and managerial implications and its limitations and opportunities for further research.
5.1 DISCUSSION OF RESULTS
The aim of this research was to investigate the influence of positive online consumer reviews on negative and positive personal experiences of consumers and what the moderating roles of the type of platform and type of message are. It was assumed that a negative personal experience would lead towards a negative online consumer review. Second, when consumers face an OCR on a third party platform, the product experience will be positively influenced. Third, when being confronted with an emotional type of OCR it is expected that the product experience would become more positive. Experience
The results gave the conclusion that a negative product experiences leads towards a higher degree of negativity in comparison with the degree of positivity of a positive experience. This is also what is found in literature about negative online consumer reviews. Negative reviews are more often posted (Anderson, 1998) and a negative review can be seen as a complaint, which in general are based on frustration from product failures. The weight (degree) of complaints is higher than the weight of compliments (Huang & Chen, 2006). So the results of this study are complementary to the theory. Platform
Third party platforms ought to have a more positive influence on prior product experiences than company owned platforms Chen & Xie (2008), Zhanga et al. (2010) and De Maeyer & Estelami (2011). The results show that this assumption is not significant. OCR’s read on third party platforms do not always ensure that consumers are more positively influenced than OCRS’s found on company owned platforms. Contradicting is when consumers have negative experiences; they feel more positive influence from company owned platforms than from third party platforms.
Message
The results show that emotional messages do not significantly influence product experience more positive than factual based messages. Consumers who faced a positive experience with a service are providing a higher rating when they are confronted with reviews based on emotional experiences. When looking at the negative experiences of consumers, a higher rating was provided with the presence of reviews based on facts.
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5.2 MANAGERIAL IMPLICATIONS
What do the results of this study imply for marketing practitioners?
Marketers could search for cooperation with third party review platforms to get permission of using their reviews on the company site. An example of this is the cooperation of kieskeurig.nl, a Dutch independent review platform, and Hi, a Dutch provider. Hi loads the reviews from kieskeurig.nl into their review platform. This way the company ensures consumers having both third party and company owned reviews in one platform.
Company owned platforms still have the name of being unreliable due to the fact that they have control of what is posted or deleted from the platform. Make clear what the process of submitting an OCR is and what you do with it. Be transparent.
Marketing campaigns should encourage consumers to share their experiences to get a more equally divided ratio between positive and negative reviews. Encouragement could be done by putting a voucher in the product package or at the final service encounter. Consumers could also be influenced to share their opinions when there is a big chance for a reward.
The fact that negative experiences result in a higher degree of dissatisfaction in comparison with positive experiences learns that firms should react on negative reviews. Consumers tend to share negative reviews easier than a positive review. Changing this negative tendency could involve an increase of more factual reviews. Known sources who share a lot of factual reviews are experts. The study provides the insight that factual based reviews are making consumers feel less negative when facing a negative experience. Another measure is to provide service recovery where possible. It is noteworthy that the range of ratings on company owned platforms are more positive than on third party websites. This suggests that managers better promote their company owned review platform as the favored review platform for their products.
Provide not only user generated OCR’s, but also make use of experts to review the product/service. Positive expert reviews influence the consumer by breaking the tendency of a negative experience into a less negative experience told in the OCR.
5.3 LIMITATIONS AND FUTURE RESEARCH
Finally, some limitations of this research should be highlighted.
The manipulation of the independent variable type of message and type of platform was not as clear as thought. The results showed that the manipulations did not lead towards significant differences among the variables type of message and type of platform. Participants did not notice a large difference between a factual or emotional message and between a third party or company owned platform.
23 Another limitation is the use of positive reviews only. If negative reviews were also included, the design would grow towards a 2x2x2x2, resulting in 16 experimental groups. For such a study this seemed to be too large to handle in this short amount of time.
Another limitation is that the questionnaire only contained one review from which participants should feel influence from. It is likely that in a more realistic situation consumers base their decisions on more than one review.
Looking at the global aspect of this topic, the Dutch community cannot be seen representative for the whole world. Cultural differences might have a huge impact on whether consumers are influenced or not.
The sample size is another limitation of this study. Only 201 respondents were used as input which cannot be seen as very representative for the worldwide community.
In this study the variables which were taking into account are not all the variables influencing consumers. There are a lot of variables of influence from where type of message, type of platform, experience, consumer expertise and credibility are just a small selection. Other variables which could be topics for future research could be the influence of experience with online consumer reviews, product involvement, etc.
24
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APPENDIX A: QUESTIONNAIRE (DUTCH ONLY)
In yellow are the options forming the eight different experimental groups as mentioned in chapter 3.
Deze enquête vormt de basis voor mijn afstudeeronderzoek naar online consumenten gedrag. Als u deze enquête zou willen invullen, zou ik dat zeer op prijs stellen.
De enquête bestaat uit een scenario van een vakantiehuis van het vakantiepark La Vallee de la Sainte Baume en een beoordeling van iemand anders waarover zeven vragen gesteld worden. Neem de tijd om u goed in te lezen. De antwoorden zullen geheel anoniem verwerkt worden. Het invullen duurt ongeveer 5 minuten.
Alvast bedankt voor de tijd en moeite!
Uw eigen ervaring met het vakantiepark La Vallee de la Sainte Baume
(Positive experience) Je hebt afgelopen zomer een luxe villa gehuurd. Het vakantiepark zag er echt prachtig uit en de villa was van topkwaliteit. Het vakantiehuis had een enorme tuin met privé zwembad en terras. De airco was ideaal met het warme weer om toch nog een goede nachtrust te hebben. Het park is super modern en van alle gemakken voorzien. Prettige bijkomstigheid is dat draadloos internet toegang gratis is. Kortom, een top vakantie!!!
(Negative experience) Je hebt afgelopen zomer een luxe villa gehuurd. Het vakantiepark zag er in de brochure werkelijk prachtig uit, van alle gemakken voorzien. Alleen bij aankomst bij de villa viel deze toch enorm tegen. De tuin was heel klein, geen zwembad wat anderen wel hadden. De kwaliteit van de bedden was zeer slecht en wanneer we dit gemeld hadden bij de receptie kregen we geen oplossing. Verder, het zwembad was wel aardig, niet te druk doordat veel huisjes een eigen zwembad hebben. Alleen het aantal ligbedden was te weinig, we konden er nooit gebruik van maken. De omgeving van het park was wel prachtig en de grote supermarkten waren op slechts 10 minuten rijden. Al met al een niet zo’n goede ervaring met La Vallee de la Sainte Baume. Wij zouden hier nooit weer naartoe gaan!
Beoordeling van La Vallee de la Sainte Baume door iemand anders
(Company owned platform) U bent op het internet aan het zoeken geweest naar wat andere mensen hebben ervaren op La Vallee de la Sainte Baume. U komt terecht op de website van La Vallee de la Sainte Baume, een website in beheer van het vakantiepark, en vind onderstaande beoordeling van Janine..
(Third party platform) U bent op het internet aan het zoeken geweest naar wat andere mensen hebben ervaren op La Vallee de la Sainte Baume. U komt terecht op Zoover.nl, een bekende onafhankelijke website waarop men een vakantie beoordeling kan plaatsen, en vind onderstaande beoordeling van Janine, een expert op het gebied van vakantiehuizen.
30
(Emotional/user message)Wij hebben in september 2011 voor 2 weken een luxe villa (zonder privé-zwembad) gehuurd. Wat een fantastisch mooie luxe en ruime villa met veel privacy en een enorm grote en mooi aangelegde tuin. Alles wat je maar kan wensen is aanwezig. Het park is prachtig aangelegd, ligt in een rustige omgeving en alle ruime luxe villa's hebben veel privacy. Het zwembad op het park was netjes met voldoende ligstoelen. Aangezien veel villa's beschikken over een privé-zwembad is het nooit erg druk aan het zwembad. De eigenaars zijn zeer gastvrij en erg vriendelijk. Iedere ochtend hangen er verse broodjes aan de voordeur. Er zijn meer dan voldoende bezienswaardigheden in de buurt en de omgeving is prachtig. Grote supermarkten vindt je op ca. 10 minuten rijden. Wij hebben een geweldige vakantie gehad en komen hier zeker nog een keer terug. Een absolute aanrader dus!
1. Wat voor beoordeling zou u uw ervaring met het vakantiehuis van La Vallee de la Sainte Baume geven?
O 1 O 2 O 3 O 4 O 5 O 6 O 7 O 8 O 9 O 10
2. Beoordeel de beoordeling van Janine op de volgende punten
Helemaal mee oneens
Mee oneens
Neutraal Mee eens Helemaal eens Geloofwaardigheid Accuraat Betrouwbaar Bevooroordeeld Compleet
3. Beoordeel de website, waarop je de beoordeling hebt gevonden op de volgende punten
Helemaal mee oneens
Mee oneens
Neutraal Mee eens Helemaal eens Geloofwaardigheid Accuraat Betrouwbaar Bevooroordeeld Compleet
4. Beoordeel Janine op hoe zij op u overkomt
Helemaal mee oneens
Mee oneens
Neutraal Mee eens Helemaal eens
31
De beoordeling van Janine is objectief
De beoordeling van Janine is geschreven vol emotie
De beoordeling van Janine geeft puur en alleen informatie
5. Beoordeel uw eigen ervaring op het gebied van het huren van vakantiehuizen door antwoord te geven op de volgende stellingen Helemaal mee oneens Mee oneens
Neutraal Mee eens Helemaal eens
Ik heb veel ervaring met het huren van vakantiehuizen op campings/vakantieparken
Ik heb veel ervaring met het huren van vakantiehuizen in het algemeen
Ik beschouw mijzelf als meer ervaren dan de gemiddelde persoon in het huren van vakantiehuizen
6. Wat is uw leeftijd?
________
7. Wat is uw geslacht?
O Man O Vrouw
32
APPENDIX B1: ANCOVA - HOMOGENEITY OF SLOPES
Tests of Between-Subjects Effects
Dependent Variable: Prod.Rating
Source Type III Sum of Squares
df Mean Square F Sig.
33
APPENDIX B2: ANCOVA RESULTS
Tests of Between-Subjects Effects
Dependent Variable: Prod.Rating
Source Type III Sum of Squares
df Mean Square F Sig.
Corrected Model 870,787a 10 87,079 114,186 ,000 Intercept 109,215 1 109,215 143,214 ,000 Cred_Platform ,968 1 ,968 1,269 ,261 Cred_Message 4,811 1 4,811 6,309 ,013 Expertise 2,909 1 2,909 3,814 ,052 Experience 450,367 1 450,367 590,567 ,000 Platform 1,529 1 1,529 2,005 ,158 Message ,000 1 ,000 ,001 ,981 Experience * Platform 2,434 1 2,434 3,192 ,076 Experience * Message 1,956 1 1,956 2,565 ,111 Platform * Message ,090 1 ,090 ,118 ,732 Experience * Platform * Message 5,230 1 5,230 6,858 ,010 Error 144,894 190 ,763 Total 8156,000 201 Corrected Total 1015,682 200 a. R Squared = ,857 (Adjusted R Squared = ,850)
Parameter Estimates
Dependent Variable: Prod.Rating
Parameter B Std. Error t Sig. 95% Confidence Interval Lower Bound Upper Bound
Intercept 2,893 ,362 7,997 ,000 2,180 3,607 Cred_Platform -,421 ,374 -1,126 ,261 -1,159 ,317 Cred_Message ,976 ,388 2,512 ,013 ,209 1,742 Expertise -,148 ,076 -1,953 ,052 -,297 ,001 [Experience=0] 3,614 ,250 14,457 ,000 3,121 4,107 [Platform=0] -,199 ,264 -,753 ,452 -,720 ,322 [Message=0] ,070 ,245 ,285 ,776 -,413 ,552 [Experience=0] * [Platform=0] -,207 ,346 -,599 ,550 -,890 ,475 [Experience=0] * [Message=0] -,234 ,348 -,672 ,502 -,921 ,453 [Platform=0] * [Message=0] -,561 ,362 -1,551 ,123 -1,275 ,153 [Experience=0] * [Platform=0] * [Message=0] 1,299 ,496 2,619 ,010 ,321 2,277
