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Online Consumer Product Reviews

(2012) (The influence of Quality, Quantity and Rating on Consumers Online Purchase Decision) (Online Consumer Product Reviews) (Sebastiaan Kooijman336606Masters Thesis MarketingErasmus University RotterdamErasmus School of EconomicsMay 2012 )

ABSTRACT

Preface

Online Consumer Product ReviewsAbstract

32 Sebastiaan Kooijman

Nowadays more and more people are using the internet to buy products and services. The most important difference from traditional shopping is that consumers cannot see, touch or try the products and services. They have to depend on the information provided by the World Wide Web. To overcome this limitation online sellers made it possible for consumers to share product evaluations online; consumer product reviews. These reviews are important for consumers in making their purchase decisions and for online sellers to increase their sales.

The influence of quality, quantity and rating in reviews on consumers online purchase decision is measured in this study. Logistic regression is used to see what influence these different aspects of reviews have. Three mayor conclusions were drawn: review quality has got a positive influence on purchase decision, purchase intention increases when the number of reviews displayed for a product increases and an increase in rating leads to an increase in purchase intention. This influence of rating is stronger when consumers are buying search goods, compared to experience goods.

Within review quality, the influence of three dimensions was tested; the presence of objective and subjective comments, product specifications and linguistic correctness of the reviews. Both the presence of information on product specifications and linguistic correctness have a positive influence on purchase decision. The presence of objective and subjective comments showed a positive influence as well, but this cannot be proven statistically.



These findings can be used by online sellers to manage the reviews on their websites. They have to take the different aspects of reviews into account when they make choices regarding the display of reviews. When they do this the right way, they can influence consumers online purchase decision and increase their sales.

PREFACE

After 5 years of studying , my days as a student are almost over. Months of intensive research have resulted in this thesis; Online consumer product reviews, The influence of quality, quantity and rating on consumers online purchase decision. This thesis is written to obtain the Masters Title in Economics and Business, Marketing, at the Erasmus University Rotterdam.

To achieve a good topic for this thesis, I have gathered a lot of information about the latest marketing trends. Many interesting topics have passed, including Experience Marketing, Behavioral Marketing, Bluecasting and Viral Marketing. Yet, this is not specific enough for people who are not daily engaged with Marketing. Therefore I have chosen a topic that is very up to date and very recognizable for a lot of people; Online consumer product reviews.

More and more people are using internet to purchase products or services and use reviews to gather information. In this thesis the influence of these reviews on consumers online purchase decision is examined.

It would not have been possible to write this thesis without the help of many people. To begin, I would like to thank my thesis supervisor, Bas Donkers, for his guidance and advice during the writing of this thesis. I would also like to thank a good friend of mine, Ruud van Sloten, for his critical notes and the many good discussions we have had about the research analysis.

Finally, special thanks goes out my girlfriend, Esther Bodegom, for her support the last couple of months. She had to deal with my bad thesis moods, but continued to support me.

May 2012

Sebastiaan Kooijman

Online Consumer Product ReviewsPreface

TABLE OF CONTENTS

ABSTRACT1

PREFACE2

TABLE OF CONTENTS3

DEFINITIONS4

1.OBJECTIVE OF THE THESIS5

1.1INTRODUCTION5

1.2AIMS AND RELEVANCE6

1.3RESEARCH OBJECTIVE & METHODOLOGY7

1.4STRUCTURE OF THE THESIS8

2.LITERATURE STUDY AND HYPOTHESES9

2.1THE INFLUENCE OF QUALITY9

2.2THE INFLUENCE OF QUANTITY11

2.3THE INFLUENCE OF RATING14

2.4CONCEPTUAL FRAMEWORK15

3.RESEARCH DESIGN AND METHOD16

3.1RESEARCH DESIGN16

3.2VARIABLES17

3.3RESEARCH METHOD19

3.4DATA CODING21

4.RESULTS AND ANALYSIS22

4.1VARIATION QUALITY, QUANTITY AND RATING22

4.2MAIN MODELS23

4.3EXTENDED MODELS27

4.4HYPOTHESES TESTING30

5.DISCUSSION31

5.1QUALITY31

5.2QUANTITY32

5.3RATING32

6.CONCLUSION32

6.1MAIN CONCLUSION32

6.2LIMITATIONS AND FUTURE RESEARCH33

LIST OF REFERENCES35

APPENDICES38

DEFINITIONS

Online consumer product reviews: Information in online stores created by consumers, based on their usage experience, opinions and evaluations. Other consumers can use this information to help them in making their purchase decision.

Online stores / shopping malls: A store / shop where products and services can be purchased via the World Wide Web.

Consumers online purchase decision (COPD): The product choice that consumers make when buying products or services in an online store / shopping mall.

Review quality: The quality of the content of the review, evaluated on the basis of the following information characteristics; subjectivity, objectivity, informativeness, understandability and linguistic correctness.

Review quantity: The number of reviews displayed in an online store for a product or service.

Review rating: The numeric value displayed at a review to evaluate the product or service.

Search goods: Search goods are defined as goods dominated by product attributes, for which consumers can acquire full information before purchase (Nelson, 1970).

Experience goods: Experience goods are goods dominated by attributes that cannot be acquired until purchase and use of the product. For those attributes information search is more costly or difficult than direct product experience (Nelson, 1970).

Online Consumer Product ReviewsTable of Contents

Online Consumer Product ReviewsDefinitions


1. OBJECTIVE OF THE THESIS

In this chapter the objective of the thesis is discussed. Consumers online purchase decision is the central topic of this thesis. The main interest lies in the influence of quality, quantity and rating of online product reviews on this decision.

This influence leads to a key question: What is the effect of quality, quantity and rating of online consumer product reviews in Dutch Web stores on Dutch consumers online purchase decision?

Based on this question the objective of the thesis arises: How can online sellers in The Netherlands manage the reviews on their websites to increase consumers actual purchases?

In paragraph 1.1 a brief description of online consumer product reviews is given. The aims and relevance of the thesis is discussed in 1.2. Paragraph 1.3 gives a summary of the research objective and methodology. The chapter ends with the structure of the thesis in 1.4.

1.1 INTRODUCTION

Nowadays more and more people are using the internet to buy products and services. On the one hand this can be explained by the fact that commercial websites are proliferating, on the other hand, because of the acceptance of on-line transactions by consumers (Hong et al., 2004). The new shopping on the World Wide Web differs from traditional shopping in many ways. The most important difference is that consumers cannot see, touch or try products or services like in traditional shopping. They are depending on the information provided by the World Wide Web. Online sellers came up with a way to overcome this limitation, they gave consumers the possibility to share product evaluations with each other online (Avery et al., 1999). In this way consumers are provided with indirect experiences of the product, which will help them in making purchase decisions. Online sellers usually provide consumers with two different kinds of product information; seller created product information and buyer created product information. The aims of this research is buyer created product information; an online consumer product review (review) is information created by consumers based on their personal usage experience, opinions and evaluations.

Half the consumers who visit web stores consider reviews as important in making their purchase decision (Piller, 1999). Consumers seek information about new products for various reasons. Goldsmith and Horowitz (2006) identify eight different reasons for consumers to seek for online opinions before purchase; to reduce risk, because others do it, to secure lower prices, access easy information, accidental/unplanned, because it is cool, stimulation by offline input such as TV and to get prepurchase information.

Online sellers provide product information as well, but there are two big differences with reviews provided by other consumers. First there is trustworthiness. Keser (2002) reports that the presence of a feedback mechanism, like product reviews, significantly increases the levels of trust and trustworthiness. Information provided by the seller is seen as less trustworthy, because they will focus on good aspects of a product and will lack information on inferior aspects.

The second difference is that consumers rely more on consumer created information, compared to seller created information. Seller created information is product orientated and objective, focusing on product attributes for many and unspecified persons (Park et al., 2007). Bonabeau (2004) states that people imitate others, not only to be accepted, but also to be safe. People may believe that other consumers have better information on the product, because they have already bought and used it. It describes usage situations, advantages and feedback from people consumers can identify with, namely other consumers. For these consumers reviews have a dual role, they inform and recommend. On the one hand it provides user generated information about the product, on the other hand it provides recommendations by users in the form of electronic word of mouth.

1.2 AIMS AND RELEVANCE

Chen and Xie (2008) state that the market of reviews is a growing one, that is becoming more and more important in consumers online purchase decision (COPD), they see it as a new type of word-of-mouth information. Amazon.com was the first to offer consumers the possibility to share their comments on products on its website in 1995. In recent years, an increasing number of online sellers followed their lead and added the possibility to write reviews on their websites. These reviews are common for different product categories such as cameras, dvd players and other electronics (search goods) and holidays, hotels, restaurants and dvds (experience goods).

With the upcoming stream of reviews the questions rises, in which way these reviews influence COPD. If online sellers do not know the answer to this question, they will not be able to manage the reviews on their website in a good way.Thereby they will miss the opportunity to give their sales a boost (Park et al., 2007). So there is an important managerial relevance to this research. Therefore the objective of the research is to find out how different aspects in reviews influence COPD, to help online sellers in The Netherlands on how to manage the reviews on their websites.

Besides a managerial relevance, the research is also valuable from a theoretical perspective, because there has been done very little research on the subject yet. Chang and Chin (2010) did research on the impact of recommendation sources on online purchase intentions. They found that reviews play an important role in online purchases. Reviews are extremely important for online sellers, because consumers base their decision on the recommendation of friends, family, colleagues and other consumers, when purchasing goods and services online. What they did not investigate is which aspects of a review actually influences COPD.

1.3 RESEARCH OBJECTIVE & METHODOLOGY

Chatterlees (2001) findings suggest that negative consumer reviews have got a deleterious impact on purchase intention, but this effect mitigates by consumers familiarity with the online seller. Consumers who choose an unfamiliar online seller, because of a lower price, are more negatively influenced by negative consumer reviews. Chatterlee looks at the influence of negative consumer reviews, but just as Chang and Chin (2010) did, he did not take a look at different aspects in reviews, to see what the influence of these aspects is on COPD.

This research investigates the influence of the aspects quality, quantity and rating of reviews on COPD and takes a closer look on experience- and search goods to see if there is a difference in influence per product group.

The research is based on prior research of Park et al. (2007), who investigated the influence of quality and quantity in reviews on COPD. Their study has several limitations. It is only based on 2 aspects in reviews (quality and quantity) and they did not make use of mixed quality reviews. That is why this research will add one aspect (rating of reviews), will take a closer look at the influence of quality and quantity (experience goods v.s. search goods) and will make use of mixed quality reviews.

The research objective is to find out how the different aspects in reviews influence COPD, to help online sellers in The Netherlands on how to manage the reviews on their websites. When they know which aspects in reviews influence COPD in a positive way, they can use this information to increase their sales.

Based on this objective the following main question arises:

What is the effect of Quality, Quantity and Rating of online consumer product reviews (in Dutch Web stores) on Dutch consumers online purchase decision?

In order to answer the main question, the research is divided into three parts. In the first part, there has been done thorough literature study on the topic. Scientific articles, relevant journals and books and the internet is used to gather the necessary information.

The second part of this thesis contains a study with a questionnaire. 137 Dutch respondents participated in this study, to see how their purchase decision is influenced by the different aspects of reviews. They all got to see seven different scenarios in which they had to choose between 2 different products in the same product category. They had to base their choice on the information provided in the two sets of product reviews. These product reviews differed in quality, quantity and rating.

To measure the effects of these aspect, Binary Logistic Regression is used to predict a model. (In chapter 3 there is a extensive description of the research methodology).

The third part of this thesis consist of the results of the study with the questionnaire and the analysis of these results.

1.4 STRUCTURE OF THE THESIS

This thesis consists of six chapters. The first two are based on gathering information on product reviews and the influence of different aspects of these reviews on COPD. The first chapter describes the objective, aims and relevance of the thesis. The second chapter focuses on prior research in the field on the influence of quality, quantity and rating and links this theory to the hypotheses. Chapter three contains a thorough description of the research model and -methodology that are used in this research. In chapter four the results and analysis are presented. Then, in chapter five the findings of the research are discussed. The thesis ends with a overall conclusion, the research limitations and possibilities for future research are discussed.

Online Consumer Product Reviews1. Objective of the thesis

Online Consumer Product Reviews1. Objective of the thesis

2. LITERATURE STUDY AND HYPOTHESES

In this literature study the focus is on the influence of reviews on COPD. Prior research on the influence of quality (2.1), quantity (2.2) and rating (2.3) on COPD will be discussed. The theory on these three aspects will be linked to the hypotheses that will be tested in this research. A conceptual framework of the research is provided in paragraph 2.4.

2.1 THE INFLUENCE OF QUALITY

Ghose and Ipeirotis (2006) did research on the quality of reviews and the influence on COPD. They found that reviews which tend to include a mixture of subjective and objective elements are considered to be more informative (helpful) for consumers.

In 2008, Ghose and Ipeirotis did further research on the topic. Their econometric analysis reveals different dimensions in reviews that influence sales and perceived usefulness. The four dimensions that stand for quality are subjectivity, informativeness, readability and linguistic correctness in reviews. In their new research they state that reviews with a mixture of objective and subjective information have a negative effect on product sales, compared to reviews with just objective or just subjective information. This is an addition to their prior research(2006). Although those reviews have a negative effect on sales, such reviews are considered more informative (helpful) for the users. An increase in the readability of reviews has a positive effect on perceived helpfulness and, for some product categories, a positive effect on product sales, while an increase in spelling errors has a negative effect on usefulness and, for some product categories, a negative effect on product sales.

Park et al. (2007) define review quality as the quality of the content of the review from the perspective of the following information characteristics; relevance, understandability, sufficiency and objectivity. This study defines subjective and emotional reviews as reviews that provide important and useful information when they are positive. Nevertheless, reviews are more persuasive if they contain understandable and objective comments with sufficient reasons of recommendation, compared to comments that expresses feelings and recommendation without specific reasons. Those reviews that are more persuasive have got a greater, positive influence on COPD.

Zhang et al. (2010) indicate that perceived informativeness and argument strength of reviews are important determinants of consumers behavioral intention, while source credibility is not. So the content of online reviews still plays an important role in consumers decision making.

As can be seen, a lot of different research is done on the influence of review quality on COPD. High quality reviews seem to have an influence on consumers purchase decision. When these reviews are positive, they will have a positive effect, but this has never been examined on de Dutch market before. So the first hypotheses of the research, based on positive reviews and the Dutch market, is:

H1: The quality of online consumer product reviews has a positive effect on consumers online purchase decision.

No prior has been done on the influence of review quality on COPD for search goods and experience goods separately, but Senecal and Nantel (2004) state that the type of product affects consumers use of information sources and the choices they make.

Nelson (1970-1974) differentiated between search and experience goods, which he later refined as search- and experience attributes, in which a goods classification was determined by its balance of the two types of attributes. Search goods are defined as those dominated by product attributes, for which consumers can acquire full information before purchase. Experience goods are those dominated by attributes that cannot be acquired until purchase and use of the product. For those attributes, information search is more costly or difficult than direct product experience.

Although there has not been any research on the influence of review quality on COPD for search- and experience goods seperately, there is a difference in what consumers find more informative, when looking at reviews for search- and experience goods.

For search goods, users prefer reviews to contain mainly objective information with a few subjective sentences. They want the reviews to confirm the validity of the product description, giving a small number of comments.

For experience goods, users prefer a brief description of the objective elements and besides that a personalized, highly sentimental positioning, describing aspects of the good that are not captured by the product description (Ghose and Ipeirotis, 2006). In this case it seems that consumers are more demanding, regarding information in reviews for experience goods, compared to search goods.

King and Balasubramanian (1994) support this theory and found that consumers assessing a search good are more likely to use own-based decision-making processes than consumers assessing an experience good and that consumers evaluating an experience good rely more on other-based and hybrid decision-making processes than consumers assessing a search product.

Although consumers are more influenced by recommendations for experience goods than for search goods (Senecal and Nantel, 2004), all of this does not immediately prove that quality of reviews has a stronger positive effect on COPD for experience goods, compared to search goods.

Petty and Cacioppo (1984) did research on the effect of strong and weak arguments on the purchase decision of people with low and high involvement. High involvement products are products for which consumers are prepared to spend more time and effort in searching for the right one. Low involvement products are products that consumers buy more frequently and will take less time to search. For high involvement products quality is more important. When looking at the search process of high involvement products, it can be compared with the search process of experience goods.

Experience goods have attributes that cannot be acquired before purchase or use and for those attributes information search is more costly or difficult. Consumers are willing to do long and difficult research for a product, when it is an experience good. This is the same for high involvement products.

Because the information search for high involvement products and experience goods looks alike, it could be true that quality is more important for experience goods (compared to search goods) as well. To find out if this influence of review quality on COPD really is stronger for experience goods, the following hypothesis is tested: .

H2: The quality of online consumer product reviews has a stronger positive effect on consumers online purchase decision when buying experience goods, compared to buying search goods.

2.2 THE INFLUENCE OF QUANTITY

According to Huang and Chen (2006) consumers are influenced in their online purchase decision by the number of positive vis- -vis negative consumer reviews. When the quantity of positive reviews is sufficiently large, they can overcome the negative attitudes of negative reviews and have a positive influence on COPD.

Park et al. (2007) and Petty and Cacioppo (1984) show that the effect of review quantity on purchase decision is stronger for consumers with low expertise than for those with high expertise. When looking at consumers in general, Petty and Cacioppo (1984) and Chen and Xie (2008) state that the number of reviews can be a signal of the popularity of a product and the number of reviews is related to an increase in the amount of product information. It is very likely that the number of reviews will lead to risk reduction for consumers, because many others have bought the product as well. Purchase intention increases when review quantity increases, so in this case, purchase intention will be positively influenced by review quantity.

Review quantity is not always positive though. Ghose and Ipeirotis (2006) investigated review quantity as well and found out that a high number of reviews for a single product makes it harder for consumers to locate the best reviews and to understand the true quality of a product. This effect is even stronger when consumers consider the average rating of a product to make their purchase decision. They will read a couple of reviews to get an impression, but will never read all of them. A high number of reviews makes it difficult for a consumer to read them and make a well informed decision on whether or not to buy the product (Hu and Liu, 2004). So prior research shows conflicting information. Chen and Xie (2008) were the last to do research on this topic and stated that a high number of positive reviews can be a signal of product popularity and can lead to risk reduction for consumers, although there is a lot of information available. When keeping their research in mind, it is possible to say that the popularity effect is heavier than the effect of having too much information when dealing with a high number of reviews. To investigate the influence of review quantity on COPD, the following hypotheses is proposed:

H3: The number of online consumer products reviews has a positive effect on consumer online purchase decision.

There has been no prior research on the difference in influence of review quantity on COPD for search- and experience goods. When looking at this difference it is important to take a closer look at the way people make decisions.

Park et al. (2007) and Petty & Cacioppo (1984) did research in which they differentiate between consumers with high- and low product expertise. Park et al. (2007) described the number of reviews as another important factor of review structure. The role of the number of review is to provide a larger amount of information and it is a signal of product popularity. Both roles are very important for consumers with low expertise, because when buying online they are depending on the information that is provided. When consumers have low expertise, they tend to rely on a peripheral cue.

They will be persuaded by a simple decision rule lots of reviews are good or by a signal of product popularity. Consumers with high expertise are not likely to be persuaded by heuristic processing (Petty & Cacioppo, 1984). This means that they will make a choice based on information that they find useful. Since experts have clear preferences for acquiring useful information, a high quantity of information can be welcome, but can also lead to a decrease in usefulness when the additional information does not fit their needs.

The effect of review quantity on consumers purchase decision is stronger for consumers with low expertise than consumers with high expertise (Park et al., 2007, Petty & Cacioppo, 1984).

To find out if the number of reviews has got a stronger positive effect on COPD when buying experience goods compared to search goods it is necessary to take a look at the expertise regarding the two product groups.

As said before, qualities of search goods can be determined prior to purchase, qualities of experience goods cannot be determined upfront. Since it is difficult, or even impossible, to evaluate experience goods before purchase, it will be more difficult to have high product expertise.

For example, almost everyone has ever been to a hotel, but you can never exactly tell what you will get. You have booked a room based on pictures and information on the website, read something about the bar and restaurant, but in the end you will just have to wait and see what it really looks like.

When buying a search product, like a camera for example, this is different. When people are shopping for search goods, it is possible to acquire full information before purchase. It is possible to see, feel and try the camera in a store before buying it online. Besides that, it is possible to take a look at the characteristics of the camera, this is not something that can be misleading, because what you see is what you get.

To find out if people really have lower expertise when buying experience goods , compared to search goods, the following hypothesis is tested:

H4a: When people are buying experience goods, they have lower product expertise, compared to buying search goods.

As said before, review quantity has a different effect on COPD for low- and high product expertise. People with low expertise are persuaded by quantity, the more the better. People with high expertise will come to a point where additional information will lead to a decrease in usefulness of this information.

When H4a is supported, it is possible, based on the findings of Park et al. (2007) and Petty & Cacioppo (1984), to state that reviews quantity has a stronger effect on COPD when buying experience goods.

This leads to the following hypothesis:

H4b: The number of online consumer product reviews has a stronger positive effect on consumers online purchase decision when buying experience goods, compared to buying search goods.

2.3 THE INFLUENCE OF RATING

Focusing on the recommender role of reviews, mostly rating is used to show product popularity (Park et al., 2007). It represents a summary of the available information and it shows an overall evaluation of the product. Mostly grades or stars are used to rate a product. Consumers consider the average rating of a product when making their decision. Reviews are either allotted an extremely high or an extremely low rating (Ghose and Ipeirotis, 2006).

Zhang et al. (2010) state that the ratings of the majority of online reviews are relatively high. This can probably be explained by the fact that products with low ratings are not purchased, thus no additional ratings are given. This leads to an average rating that may not be very valuable to a potential buyer, because in this case the reader has to read the reviews to see which are actually of interest. What usually happens in this case is that buyers will read a couple of reviews in order to form a decision regarding the product, based on the rating and content of the reviews (Ghose and Ipeirotis, 2006). Especially low involved consumers are influenced by high ratings in reviews. Since they can easily know how other people think about a product through this tool, they can predict a products popularity. This will increase their purchase intention (park et al. 2007).

Based on prior research it is expected that products with a high rating will have a positive effect on COPD. That is why the following hypotheses is tested:

H5: The rating of online consumer product reviews has a positive effect on consumers online purchase decision.

2.4 CONCEPTUAL FRAMEWORK

(EXPERIENCE-V.SSEARCH GOODS) (EXPERIENCE-V.SSEARCH GOODS)

H2 : ++H4 : ++

(CONSUMERS ONLINE PURCHASE DECISION) (REVIEW QUALITY) (REVIEW QUANTITY) H1 : + H3 : + H2 : +

H5 : +

(REVIEW RATING)

Figure 2.4. Conceptual framework.

Online Consumer Product Reviews2. Literature study and Hypotheses

Online Consumer Product Reviews2. Literature study and Hypotheses

3. RESEARCH DESIGN AND METHOD

In the first 2 chapters the introduction and theoretical framework are discussed. In chapter 1 a brief description of the thesis methodology is displayed. This chapter contains a detailed description of the research design and -method, which starts with the research design in 3.1. In the next paragraph (3.2) the variables used in the research emerge. The chapter ends with the method used in the research (3.3) and the data coding in 3.4.

3.1 RESEARCH DESIGN

To be able to give an answer to the research question, the hypotheses are tested empirically with the help of a questionnaire among Dutch consumers.

137 respondents participated. Their average age was 34 and the distribution of men and women was 51.1% and 48.9%. A large part of the respondents (94,2%) already had experience with buying products online and with using product reviews to help making their decision. (See appendix 1 for sample statistics).

A set of online product reviews was provided for each respondent in the research. The respondents got to see 7 or 9 different scenarios, containing two different sets of online consumer product reviews for similar products (experience and search) in web stores. Their purchase intention was tested regarding the products. (See appendix 2 for examples of the review sets).

The experimental products used in this research are a television and a digital camera (search goods) and a hotel and a vacation (experience goods). These products were chosen based on a focus group interview (15 subjects). These products were purchased online by 80% of the subject at least once. Note: the subjects in the focus group interview did not participate in the research.

The sets of reviews differed in quality, quantity and rating. Respondents had to indicate which of the two products they would buy, based on the information provided in the two sets of reviews. The different sets of reviews that respondents got to see were based on real life reviews, but at some points slightly modified in order to be able to test the actual influence of the different reviews aspects on COPD. To make sure there was no interference of interaction effects, the influence of review quality and quantity was measured separately.

Half of the respondents got a questionnaire based on quality and rating, the other half got a questionnaire based on quantity and rating. Respondents were randomly assigned to one of the questionnaires.

The web store contained information provided by the seller and information provided by consumers (reviews). The seller-created information for the search goods consisted of a picture of the product and a few product characteristics. For the experience products a picture was provided in combination with a brief description.

The online consumer product reviews used in the research were based on real reviews from online web stores. They contained the name and avatar of the reviewer (when provided), the date it was posted, a title and the actual content. The length of reviews can influence the perception of quality and quantity (Chevalier and Mayzlin, 2006) and was therefore fixed. Each review consisted of 3 lines, exclusive title.

At last, the respondents were asked how experienced they were with buying the experimental products and using reviews to gather information about these products. This has made it possible to see if the respondents were high or low experienced regarding on the one hand search goods and on the other experience goods.

3.2 VARIABLES

The independent variables used in this research are review quality (high low), review quantity (few moderate) and review rating (high low). The dependent variable is purchase decision.

Independent variables

There are a lot of criteria to measure review quality. In this research the criteria for review quality were based on prior research in this field. Subjectivity, objectivity, informativeness, understandability and linguistic correctness were chosen as these criteria.

Reviews of high quality contain a mix of subjective and objective comments, are understandably written without spelling errors and give sufficient product information. Figure 3.2.1. is an example of a high quality review.

Peter 22-03-2012

Perfect camera specifications and pictures

This camera makes amazing pictures with his 10 megapixels. You can see them right away on the 4 inch screen. Best tested by Consumentenbond.

Figure 3.2.1. High quality review.

Low quality reviews display emotional feelings instead of product information, contain spelling errors and are merely subjective. Figure 3.2.2. is an example of a low quality review.

Juan 22-03-2012

Woooow this camera is awesome

This really is the best camera ever. Ive wntedd it for months, but now I finally have it. Cant wait to go on a holliday and make the best pictures ever.

Figure 3.2.2. Low quality review.

In this research the reviews could score points on all three criteria; objective/subjective comments, information on product specifications (informativeness) and linguistic correctness (understandable comments without spelling errors). This resulted in an average score for each set of reviews. Example: a set of 7 product reviews, with 5 reviews scoring 2 points and 2 reviews scoring 1 point. So the set scored 12 point out of 21, which lead to an average score of 0,57.

To check whether or not the review sets with high(er) quality and low(er) quality were perceived as such, the subjects in the focus group interview were asked to value the different review sets per scenario. Only the scenarios were used where the respondents valuated the higher quality review sets and lower quality review sets as such.

Review quantity is based on the conducted focus group interview. The subjects were asked their opinion about what they think is few and what is moderate regarding review quantity. This resulted in a number between 1-8 as few and a number between 10-25 as moderate. In this research a number of 7 reviews was selected as few, 20 reviews as moderate.

To determine what is high and what is low in review rating, three Dutch online web stores were viewed (Vergelijk.nl, Bol.com and Kieskeurig.nl). When looking at products like cameras and televisions, most of the grades are between 7,0 and 9,0. When looking at hotels and vacations, the grades varied between 6,0 and 9,0. In this research the ratings used were in these ranges, where for each scenario one of the two sets of reviews got a higher grade than the other.

Dependent variable

Consumers online purchase decision was measured by making respondents choose between one of two products. As said before, the sets of reviews provided for the products differed in quality, quantity and rating. Respondents were asked which of the two products they would buy, based on the available information.

Control variables

The experiment could be affected by the characteristics of brand names, prices, product design and specifications (Hong et al. 2004). In order to improve the internal validity of the research the possible effects of these variables were controlled. To make sure there was no brand effect, the brand names were removed. Price was left out of the research so the respondents choice would not be influenced by price. Product specifications were the same for all the products in each product group and product design was kept almost identical.

3.3 RESEARCH METHOD

A logistic regression model is used to determine how consumers online purchase decision is influenced by quality, quantity and rating of reviews. When online sellers know how these characteristics influence purchase decision, they are able to customize their strategies regarding the display of reviews on their websites. In this way they can increase their sales numbers.

The respondents experience regarding the online purchase process of search- and experience goods was measured on a 5-point Likert scale, varying from a lot experience to no experience at all. With a T-test the means were compared to see for which purchase process the respondents expertise was higher.

Logistic regression models

The main model contains the dependent variable purchase decision and the independent variables quality, quantity and rating.

The equation of the model is as follows:

With this model it is possible to see the influence of the independent variables on the dependent variable.

When looking at the difference between search- and experience goods, the dataset is divided into two parts. One model is created for search goods and one model is created for experience goods.

The equations of the main models for search- and experience goods are as follows: .

.

.

With these models it is possible to see the influence of the independent variables on the dependent variable for search- and experience goods separately.

Next, the model is extended with the three different dimensions of quality; objective/subjective comments, information on product specifications (informativeness) and linguistic correctness.

Now the equation of the main model is: .

.

And the equations of the main models for search- and experience goods are: .

With the models above, it is possible to test the hypotheses regarding the influence of quality, quantity and rating on consumers online purchase decision. When looking at the difference between search- and experience goods and the extent to which both product groups are influenced by the independent variables, it is necessary to look at the interaction effects. Including interaction effects in the model makes it possible to test the hypotheses regarding the difference in influence of quality and quantity for search- and experience goods.

The equation for the main model, including interaction effects, is:

The equation for the model with the three dimensions of quality, including interaction effects, is:

3.4 DATA CODING

As said before, the respondents got to see different scenarios where they had to make a choice between two different products. The product on the left was coded as 0 and the product on the right as 1. Each choice they made was based on the difference in quality, quantity and rating between the two sets of reviews provided with the products. Quality was coded between 1 and 0, with 1 as the highest possible quality and 0 as the lowest. This was the same for the different dimensions of quality; objective/subjective comments, information on product specifications and linguistic correctness. For quantity and rating absolute values were used.

Dummy variables were created to measure the difference in influence of quality, quantity and rating for search- and experience goods. These dummy variables were created by multiplying the three aspects with the type of product, with search goods coded as 0 and experience goods coded as 1 (Field, 2005 and Aaker & Keller, 1990).

To see whether or not there was a difference between product expertise for search- and experience goods the respondents got to answer two questions about their expertise. One concerning previous online purchase of the products and the other concerning the usage of product reviews when buying such products. The options were coded: a lot of experience as 1, experience as 2, not much, not little experience as 3, little experience as 4 and no experience as 5.

Online Consumer Product Reviews3. Research design and Method

Online Consumer Product Reviews3. Research design and Model

4. RESULTS AND ANALYSIS

The results of the study are divided into 2 parts, the first part shows the regression models were the influence of quality, quantity and rating is measured (paragraph 4.2). With these models it is possible to answer hypotheses 1 to 5. Paragraph 4.3 shows the regression models, including the three different dimensions of quality. These models make it possible to see whether or not there is a different influence within quality. An overview of the hypotheses and the analysis is shown in 4.4. This chapter starts with the variation in quality, quantity and rating (4.1).

4.1 VARIATION QUALITY, QUANTITY AND RATING

Table 4.1 shows the variation in quality, quantity and rating of the different review sets used in the research.

Minimum

Maximum

Mean

Std. Deviation

Quality

.000

.333

.196

.106

Quantity

.000

13.000

7.449

6.018

Rating

.000

1.000

.528

.599

Table 4.1: Variation in quality, quantity and rating.

As said before, the respondents got to see different scenarios with two sets of reviews. They had to indicate which of the two products they would buy, based on the available information. The biggest difference in quality of two review sets used in the scenarios is .333. There were also scenarios where the two review sets had the same quality (.000). The mean variation for quality is .196. For quantity, the minimum and maximum values are .000 and 13.000, with a mean of 7.449. For rating respectively, these numbers are .000, 1.000 and .549.

So in this research, variation is highest for quantity and lowest for quality.

4.2 MAIN MODELS

The influence of quality, quantity and rating of reviews on COPD can be obtained from the different regression models. In the first model quality, quantity and rating are presented (table 4.2.1).

Coefficient

Std. Error

Constant

-.024

.454

Quality

3.680*

.009

Quantity

.072*

.168

Rating

1.195*

.075

Dependent variable is Choice Product 1.*Significant at .05 level

Table 4.2.1: Coefficients main model

Table 4.2.1 shows that quality, quantity and rating are all significant and positive. Quality in reviews has a positive influence (3.680) on the choice that consumers make when buying goods in an online environment. Quantity and rating respectively have a positive influence of .072 and 1.195. When quality of reviews increases with .10, the utility will increase with .368. Including an additional reviews to a product will increase utility with .072. When the average rating of a product, obtained from the reviews, increases with 1 point, the utility will increase with 1.195. When looking at the variation means in table 4.1 and the coefficients in 4.2.1 we can see that average utility in this research increases the most by quality and the least by quantity.

These numbers indicate that all three aspects have got a positive influence on consumers online purchase decision. However, this is a general model and contains both choices regarding search- and experience goods.

When dividing the data into two sections, choices regarding search- and regarding experience goods, it is possible to see if significance changes when consumers choice is focused on just one of the two product types. This can be seen in figure 4.2.2 and 4.2.3.

Coefficient

Std. Error

Constant

-.189

.140

Quality

3.730*

.526

Quantity

.086*

.018

Rating

1.353*

.306

Dependent variable is Choice Product 1.*Significant at .05 level

Table 4.2.2: Coefficients main model, search goods

The independent variables have a significant, positive influence on the dependent variable. When consumers are buying search goods online and using reviews, the aspects quality (3.370), quantity (.086) and rating (1.353) of these reviews will have a positive effect on their purchase decision. When quality, quantity or the rating of reviews for a product increases, consumers are more likely to buy it.

When consumers are buying experience goods online the model changes, but the influence of the different aspects in reviews are still significant and positive.

Coefficient

Std. Error

Constant

.253**

.145

Quality

5.486*

1.226

Quantity

.082*

.013

Rating

1.084*

.208

Dependent variable is Choice Product 1.*Significant at .05 level** Significant at .10 level

Table 4.2.3: Coefficients main model, experience goods

Different from the other models is the coefficient of the constant. In table 4.2.3 the coefficient is positive (.253) and insignificant at a .05 level, but significant at a .10 level. Quality, quantity and rating have values of respectively 5.486, .082 and 1.084.

All three models above conclude that hypotheses 1, 3 and 5 are supported.

Before testing hypotheses 2 and 4b it is necessary to test hypothesis 4a; consumers have more product expertise when buying search goods, compared to experience goods. Expertise regarding the purchase process was measured. Table 4.2.4 shows the results.

Buying process

Mean

Search goods

3.515

Experience goods

2.545

Test for Equality variances

F

Sig.

T

Sig. (2-tailed)

Mean difference

Equal variances assumed

15.190

.000

6.285

.000

.97015

Equal variances not assumed

6.285

.000

.97015

Table 4.2.4: T-test for equality of means.

The t-test for equality of means shows us that there is a significant difference between respondents expertise regarding the purchase process of search- and experience goods. Data was coded from 1 till 5, with 1 representing a lot of expertise and 5 no expertise at all. When comparing the means, the expertise regarding experience goods is higher than the expertise regarding search goods (difference of .97015). Therefore we can conclude that hypotheses 4a is not supported. Consumers do not have higher expertise when buying search goods. Actually it is the other way around, they have more expertise when buying experience goods.

The question that rises is: does this mean that quantity does not have got a stronger positive influence on purchase decision when buying experience goods? (H4b). Park et al. (2007) and Petty & Cacioppo (1984) state that the effect of review quantity on COPD is stronger for consumers with low expertise than for consumers with high expertise.

With including interaction effects in the model it is possible to see the difference in influence between search- and experience goods. This makes it possible to test for hypotheses 2 and 4b.

The positive influence of quality, quantity and rating on COPD is proven, for both the general model as the models for search- and experience goods. Now dummys are included to test for interaction effects.

When including dummys in our model the coefficients are:

Coefficient

Std. Error

Constant

.033

.100

Quality

3.807*

.535

Quantity

.069*

.017

Rating

1.609*

.299

Quality*Experience goods

.559

1.193

Quantity*Experience goods

.003

.022

Rating*Experience goods

-.612**

.350


Table 4.2.5: Coefficients main model, including interaction effects

With the addition of interaction effects, it is possible to see if one of the aspects has a stronger positive influence on purchase decision when buying search- or experience goods. Table 4.2.5 shows that the influence of quality and quantity is stronger positive when buying experience goods, compared to search goods (.559 and .003). However, these results do not support hypotheses 2 and 4. The coefficients do not have a significant influence and therefore the hypotheses cannot be accepted. Rating has got a negative coefficient, what implicates that rating has got a stronger positive influence on purchase decision when buying search goods, compared to experience goods. In addition, this influence is actually significant at a .10 level.

4.3 EXTENDED MODELS

Coefficient

Std. Error

Constant

.025

1.092

Objective/Subjective

.769

.535

Product specifications

1.109

.810

Linguistic correctness

2.643*

1.112

Quantity

.072*

.009

Rating

1.162*

.184

In the extended models quality is divided into three dimensions, objective/subjective comments, information on product specifications and linguistic correctness.

Dependent variable is Choice Product 1.*Significant at a .05 level

Table 4.3.1: Coefficients extended model.

Table 4.3.1 shows that all three dimensions of quality have a positive influence on purchase decision. The presence of both objective and subjective comments in a reviews has a positive influence (.769), but is not significant at a .05 or .10 level. The addition of product specifications in a reviews has a positive influence as well (1.109), but this influence is not significant either. The only aspect of quality with a positive and significant influence is linguistic correctness (2.643). Both quality and rating have, like in the main model, a positive, significant influence on purchase decision (.072 and 1.162).

To see whether or not there is a difference in influence when testing for both product types separately, a model for search- and a model for experience goods are estimated. Results are presented in table 4.3.2 (search goods) and table 4.3.3. (experience goods).

Coefficient

Std. Error

Constant

.021

.220


-2,498

3.123


3.170**

1.797


6.643

4.928

Quantity

.070*

.022

Rating

1.681*

.532

Dependent variable is Choice Product 1.*Significant at a .05 level** Significant at a .10 level

Table 4.3.2: Coefficients extended model, search goods.

The extended model for search goods shows that the influence of quantity and rating is still significantly positive (.070 and 1.681). Different from the previous model is the influence of the dimensions of quality. The presence of both objective and subjective comments in a review has a negative influence on purchase decision (-2.498), but is not significant. Product specifications and linguistic correctness in reviews both have a positive influence (3.170 and 6.643), but only the presence of products characteristics has a significant influence (at a .10 level).

Coefficient

Std. Error

Constant

.251**

.149


2.576

2.807


3.299**

1.888


-

-

Quantity

.082*

.013

Rating

1.083*

.208

Dependent variable is Choice Product 1.*Significant at a .05 level** Significant at a .10 level

Table 4.3.3: Coefficients extended model, experience goods.

The extended model for experience goods shows that the influence of quantity and rating keeps being significantly positive (.082 and 1.083). The dimensions of quality do show a difference, compared to the model for search goods. Linguistic correctness is left out of the model due to very high, significant correlation ( > 0.93) with objective/subjective comments (.93) and the presence of product specifications (.99). The presence of objective and subjective comments show a significant, positive influence (2.576), while the presence of product specifications has a significant, positive influence at a .10 level (3.299). Nevertheless, due to the high correlation it is not possible to determine which of the dimensions of quality actually causes the effect on COPD. So it is not possible to draw accurate conclusions on the influence of these dimensions.

When including interaction effects it is possible to test if there is a difference in influence on purchase decision between the two products groups.

When including dummys in our model the coefficients are:

Coefficient

Std. Error

Constant

.180

.121


-4.179**

2.441


4.034*

1.490


9.174*

3.998

Quantity

.057*

0.017

Rating

1.894*

.469

Objective/Subjective * Experience goods

1.705

3.208

Product specifications * Experience goods

-7.633**

4.340

Linguistic correctness * Experience goods

-

-

Quantity * Experience goods

.021

.024

Rating * Experience goods

-.840**

0.496


Table 4.3.4: Coefficients extended model, including interaction effects.

Table 4.3.4 shows that quantity has a stronger positive influence when buying experience goods, but this influence is not significant. Rating has a significantly, stronger, positive influence on purchase decision when buying search goods.

When looking at the three dimensions of quality you can see that objective and subjective comments in a review have a more positive influence on purchase decision when buying experience goods, but this influence is not significant. Product specifications have got a less positive influence when buying experience goods, compared to search goods. This influence is significant at a .10 level. As in the previous model, linguistic correctness is left out of the model due to very high, significant correlation ( > 0.94) with objective/subjective comments (.93) and the presence of product specifications (.99). Therefore the findings above cannot be assumed. With these data it is not possible to accurately determine which of the three dimensions actually causes the influence on COPD. No accurate conclusions can be drawn on the effect of the three dimensions of quality.

4.4 HYPOTHESES TESTING

Based on the findings in paragraph 4.2 and 4.3 the hypotheses are empirically tested. Table 4.4.1 gives an overview.

Hypotheses

Supported / not supported

H1: The quality of online consumer product reviews has a positive effect on consumers online purchase decision.

Supported

H2: The quality of online consumer product reviews has a stronger positive effect on consumers online purchase decision when buying experience goods, compared to buying search goods.

Not supported

H3: The number of online consumer product reviews has a positive effect on consumers online purchase decision.

Supported

H4a: When people are buying experience goods, they have lower product expertise, compared to buying search goods.

Not supported

H4b: The number of online consumer product reviews has a stronger positive effect on consumers online purchase decision when buying experience goods, compared to buying search goods.

Not supported

H5: The rating of online consumer product reviews has a positive effect on consumers online purchase decision.

Supported

Table 4.4: Testing the hypotheses

Online Consumer Product Reviews4. Results and Analysis

Online Consumer Product Reviews4. Results and Analysis

5. DISCUSSION

This research shows three major findings concerning the influence of quality, quantity and rating in reviews on consumers online purchase decision. Besides those three findings the research shows more results, but these results do not have a significant influence. In this chapter the research results are discussed. Paragraph 5.1 discusses the influence of quality, 5.2 quantity and 5.3 rating.

5.1 QUALITY

The quality of online consumer reviews has a positive effect on COPD. Reviews of high quality contain a mix of subjective and objective comments, are understandably written without spelling errors and give sufficient product information.

The main regression models showed that quality has a positive influence on COPD for both search- and experience goods. Interaction effects were included to see if there was a difference in the degree of influence between search- and experience goods. This model implicated that quality in reviews has a stronger effect on purchase decision when people are looking for experience goods online. Nevertheless, this hypotheses could not be supported, due to insignificance of the effect. When looking at the theory of Ghose and Ipeirotis (2006) and Petty and Cacioppo (1984) the hypothesis could still be a plausible one. When people are not able to gather information about all attributes before purchase, they have to depend on the information provided in reviews. If these reviews are of poor quality, it would be harder to make a choice. It could be possible that this hypotheses is supported when other experimental products are used in a new research.

When looking at the different dimensions of quality, it is seen that there are different outcomes. The main model showed that the inclusion of all three dimensions; objective and subjective comments, information on product specifications and linguistic correctness, has a positive influence on COPD. A side note here is that linguistic correctness is the only dimension with a significant, positive influence. So no conclusions can be drawn with regard to objective and subjective comments and information on product specifications.

The same applies to the main models for search- and experience goods. It is hard to draw conclusions about the influence of the different aspect, due to lack of significance. For both models the only aspect with a significant influence is information on product specifications. However, this influence is positive for both models.

The model, including interaction effect, clarifies some things. All three aspects have a significant influence at a .10 level. Both products specifications and linguistic correctness have a positive influence, the presence of objective and subjective comments a negative one. In this way it is nevertheless possible to determine the influence of the different dimensions of quality. With these data it is not possible to draw conclusions regarding the effect of the three dimensions on COPD when buying search goods on the one hand and experience goods on the other. Due to high correlation of linguistic correctness, with both objective and subjective comments and product specifications, it is not possible to find which of the dimensions actually causes the effect on COPD.

5.2 QUANTITY

Second, COPD is positively influenced by reviews quantity. When the number of reviews increases, the positive influence on COPD increases as well. Yet there is a point where an additional review will lead to a decrease of usefulness. As Ghose and Ipeirotis (2006) and Hu and Liu (2004) stated, a high number of reviews for a single product makes it harder for consumers to locate the best reviews and understand the true quality of the product. This effect is even stronger when consumers consider the average rating as well, when making their purchase decision. The point where the positive influence of review quantity stops and becomes negative is not included in the study due to fixed values for quantity (7 and 20). It is possible to investigate whether or not there is such a point and where it is, then a bigger variation in the number of reviews is needed.

5.3 RATING

As is seen in the previous chapter, rating positively influences COPD. A higher rating leads to an increase in purchase intention. When buying search goods this influence is stronger positive than when buying experience goods. As said before, this could be different when other experimental products are chosen as search- and experience goods.

Online Consumer Product Reviews5. Discussion

Online Consumer Product Reviews5. Discussion

6. CONCLUSION

This chapter describes the way online sellers should manage their online reviews. In 6.1 a conclusion regarding the results is displayed. Every study has its limitations. In 6.2 these limitations and their possibilities for future research are discussed.

6.1 MAIN CONCLUSION

This study investigated the influence of several aspect of reviews on COPD. The results show how important it is for online sellers in the Netherlands to properly manage their online reviews. Previously only online sellers provided consumers information about products, but since Amazon.com made it possible for consumers to write about their experiences, the online sellers lost some control over consumers. Now they are able to read what other consumers, who are just like them, but who have already bought the product, think of it.

Since quality has a positive influence on COPD, the online sellers have got to find a way to make consumers write high quality reviews. This can be achieved by rewarding consumers who write high quality reviews with some sort of point, which they can use to get a discount for example.

When online sellers want to increase product sales they can give reviews points on quality. Then they can show reviews sorted from high quality to low quality. The study showed that quality in reviews is very important in consumers purchase decision. Displaying high to low quality will be valuable for both the online seller as the consumers, COPD will be positively influenced and consumers will have to read far less to obtain the same amount of information. The dimensions of quality (product specifications and linguistic correctness) have a significant, positive influence on COPD, objective and subjective comments has a positive, but insignificant effect. These dimensions (the two significant anyway)can be used as drivers to give points for quality.

Quantity has a positive influence on COPD as well, but it is uncertain when additional reviews will have an adverse effect (Ghose and Ipeirotis,2006 and Hu and Liu,2004). Therefore it is recommended to give a short summary for each set of reviews, containing the number of reviews, the quality and the average rating. Consumers can see at a glance how good (popular) a product is and they can use the high quality reviews, which are at the top, to gather the desired information.

Besides the display of rating in the summary, it is recommended to emphasize the rating in review sets of search goods. Although rating has a positive influence on COPD for both search- and experience goods, this influence is stronger for consumers who are buying search goods.

6.2 LIMITATIONS AND FUTURE RESEARCH

As said before, every research has its limitations. When evaluating this research , some limitations have to be taken into account.

In this research the influence of three aspects in reviews were taken into account; quality, quantity and rating. Naturally there are more aspects that can be used in future research. To increase reliability of the results, in future research more review aspects can be taken into account.

Another limitation is that negative reviews were not used. The reason to leave negative reviews out if the research was to make sure the effect of quality, quantity and rating were measured accurately and side effects were prevented. The same applies for the length of the reviews. In this research the length was fixed at three lines. Variation in the number of lines will have an effect on the usefulness of a review and therefore also on COPD.

As can be seen in chapter 4, a lot of effects were positive on COPD, but could not be used due insignificance. 137 respondents conducted the research, but when more respondents participate, it could be possible that more significant effects arise. This will naturally have a positive effect on the research reliability as well. If it is hard to find consumers willing to participate, it is a good idea to use a conjoint analysis. One of the main advantages of this research method is that it can obtain accurate results from a relatively small sample.

The experimental products used in this research were a television and a digital camera (search goods) and a vacation and a night at a hotel (experience goods). One of the biggest disadvantages of these products is the expertise the respondents had regarding the purchase process. Nowadays a lot of people search for vacations or hotels online, because it is (practically) impossible to do it at the actual location. For products like a television or camera people are willing to go to a store to take a look first. The results regarding search- and experience goods could change when using other products for both product groups.

An additional limitation is the fact that respondents got to see 7 or 9 different scenarios, from which they had to choose between 2 products. This is not realistic, while in real life this situation would never occur. Besides that, it could be possible that respondents are influenced by prior choices they made. For this reason it is valuable to use one scenario per respondent. The downside of this approach is that you will need a very large number of participants.

The extended models in chapter 4 did not show the effects of all three dimensions of quality due to high correlation. This can be prevented by a better design of the questionnaire. This will lower the correlation and makes it possible to get a better estimate of the dimensions of quality.

The last important limitation concerns review quantity. As seen in the research, quantity has got a positive influence on COPD, but as Ghose and Ipeirotis,2006 and Hu and Liu,2004 have examined, there is a point where additional reviews will have an adverse effect and will have a negative influence. In this research the quantity was fixed at 7 and 20. When the amount of reviews varies, it is possible to find the point where the positive influence of quantity turns into a negative influence.

Online Consumer Product Reviews6. Conclusion

Online Consumer Product Reviews6. Conclusion


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Website References:

www.bol.com

www.kieskeurig.nl

www.nachtjeweg.nl

www.prijsvergelijk.nl

www.vergelijk.nl

Online Consumer Product ReviewsList of References

Online Consumer Product ReviewsList of References

www.weekendjeweg.nl

APPENDICES

Appendix 1: Respondents sample statistics

Online Consumer Product ReviewsAppendices

Appendix 2: Examples of review sets

APPENDIX 1: RESPONDENTS SAMPLE STATISTICS

Online Consumer Product ReviewsAppendix 1.

Online Consumer Product ReviewsAppendix 1.

APPENDIX 2: EXAMPLES OF REVIEW SETS

(General quality: 0,381Objective / subjective comments: 0,286Product specifications: 0,286Linguistic correctness: 0,571Quantity: 7Rating: -) (General quality: 0,714Objective / subjective comments: 0,714Product specifications: 0,714Linguistic correctness: 0,714Quantity: 7Rating: -)

(General quality: 0,762Objective / subjective comments: 0,714Product specifications: 0,857Linguistic correctness: 0,714Quantity: 7Rating: 7,3) (General quality: 0,476Objective / subjective comments: 0,429Product specifications: 0,286Linguistic correctness: 0,0,714Quantity: 7Rating: 8,0)

Online Consumer Product ReviewsAppendix 2


(General quality: 0,62Objective / subjective comments: 0,57Product specifications: 0,71Linguistic correctness: 0,57Quantity: 7Rating: 7,8) (General quality: 0,65Objective / subjective comments: 0,6Product specifications: 0,65Linguistic correctness: 0,7Quantity: 20Rating: 7,0)


Gender

Gender

70 respondents 51%

67 respondents 49%

MaleFemale0.511000000000000010.48900000000000027

Age

18-25 years26-30 years31-35 years36-40 years41-50 yearsOlder than 50 years0.190.29200000000000029.5000000000000043E-28.8000000000000064E-20.212000000000000110.12400000000000005

Experience with online purchases and use of reviews

129 respondents 94%

8 respondents 6%

ExperienceNo Experience0.941999999999999955.8000000000000003E-2

Online Consumer Product Reviews Sebastiaan (33… · Web viewOnline Consumer Product...

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