Whose online reviews to trust? – Understanding reviewer trustworthiness and its impact on business

The advent of the Internet has radically changed the way in which consumers can receive information about products they consider purchasing. While years ago we could only trust the opinion of our relatives and friends who have already used the product in question, or the information provided by the seller (though highly likely to be biased), nowadays we have an easy access to a great number of online reviews for various products and services. In popular websites like Amazon, TripAdvisor and IMDB people can find reviews for everything from camping lanterns, to places where to eat in Mexico City, or the new movie starring Leo diCaprio. This has become possible due to the rise of the so-called electronic word-of-month (e-WOM), or the phenomenon of people sharing with peers their opinions and experiences with certain products and services over the Internet.

Studies show that the impact of online reviews on sales of products and services is considerable (Forman and Wiesenfeld, 2008; Duan and Winston, 2008). A number of scholars claim that factors such as the length of the online review, the style of writing and the content affect the strength of the influence of the review on the purchasing decision of the customer (Otterbacher, 2009; Liu et al., 2008). However, little focus has been put on the impact of the person who writes the reviews.

With this in mind, Banerjee et al. (2017) took the research endeavor to investigate whether the overall trustworthiness of reviewers has any impact on the number of customers visiting the business that has been reviewed, and also which reviewer characteristics determine the trustworthiness of the reviewer. In order to achieve this goal, the authors used as a foundation the Source Credibility Theory (SCT), which argues that the trustworthiness of the information source improves the perceived credibility of the source, and as a consequence the persuasiveness of the communication in online reviews. Using a dataset with more than 2.2 million observations from Yelp.com the authors tested two sets of hypotheses, one assessing whether the online reputation of the business leads to higher business patronages and whether this is moderated by the trustworthiness of the reviewers, and the second set testing what factors impact the trustworthiness of the reviewers.

Summary of findings



1a: Review-based online reputation of a business is positively associated with the patronages generated by the business.


1b: Average perceived trustworthiness of reviewers reviewing a business positively moderates the association between online reputation and patronages of the business.


2a: Reviewer’s positivity in rating businesses is positively associated with the perceived reviewer trustworthiness.


2b: The amount of reviewer’s involvement in reviewing businesses is positively associated with the perceived reviewer trustworthiness.


2c: Reviewer’s experience in an online review website is positively associated with the perceived reviewer trustworthiness.



2d: Reviewer’s reputation in an online review website is positively associated with the perceived reviewer trustworthiness.


2e: Reviewer’s competence in writing useful reviews is positively associated with the perceived reviewer trustworthiness.


2f: Reviewer’s sociability as perceived by other users of a review website is positively associated with the perceived reviewer trustworthiness.


Table 1. Summary Results

Relevance, strengths and weaknesses

A strong point of the paper by Banerjee et al. (2017) can be traced to the academic contributions that it makes. The study is the first to integrate in one model various reviewer characteristics that have an impact on the trustworthiness. Contrary to previous studies that examine the phenomenon based on one or two characteristics, the authors of the paper use six different attributes; hence they study trustworthiness from various different angles and provide a more complete understanding of the factors that influence it. Additionally, the paper has strong managerial implications, as it presents evidence that businesses are impacted by their online reputation. Therefore, management should encourage the regular submission of reviews from their customers, but should also ensure that their customers are satisfied with their products, so that the reviews submitted are positively inclined. Moreover, as the study finds that trustworthiness of the reviewer increases the strength of the relationship between online business reputation and business patronages, managers should try to find ways in which they can encourage the most trustworthy reviewers to submit reviews.

On the other hand, the study does not come without limitations. A weakness of the paper is that when it considers the impact of online review reputation of a business, they only account for the increase in the business patronages, measured as the number of check-ins, but they do not provide evidence whether this increase leads to more tangible benefits such as increase in sales. Additionally, although a number of characteristics are considered that impact the trustworthiness of the reviewer, the list is arguably far from exhaustive. Certain cues such as whether the profile of the reviewer has a picture, for example, were ignored by the authors but can arguably also impact the findings of the study. Finally, the paper is based on data solely from one website, which decreases the generalizability of the findings. This, however, provides directions for future research, as the findings made by this paper can be tested in other websites/platforms where the importance of online reviews is high, such as TripAdvisor, Booking.com, etc.

Sources used:

Banerjee, S., Bhattacharyya, S. and Bose, I. (2017). Whose online reviews to trust? Understanding reviewer trustworthiness and its impact on business. Decision Support Systems, 96, pp.17-26.

Duan, W., Gu, B. and Whinston, A. (2008). Do online reviews matter? — An empirical investigation of panel data. Decision Support Systems, 45(4), pp.1007-1016.

Forman, C., Ghose, A. and Wiesenfeld, B. (2008). Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets. Information Systems Research, 19(3), pp.291-313.

Liu, Y., Huang, X., An, A. and Yu, X. (2008). Modeling and Predicting the Helpfulness of Online Reviews. 2008 Eighth IEEE International Conference on Data Mining.

Otterbacher, J. (2009). ‘Helpfulness’ in online communities. Proceedings of the 27th international conference on Human factors in computing systems – CHI 09.








Online commerce and new retail: A discussion of the emergence of social commerce and service commerce in China

“New retail” is the most searched word started form 2017 but showing a decreasing trend in the recent two months. Momentum is slowing down on the concept of new retail instead, people started to chase the other popular concept (e.g. autonomous retail). However, the believers argue that the transformation of retail industry will occur in the near future. To discuss new retail, we need to clarify some concept in advance.

What is new retail?

The traditional retail experienced several transition phase, namely real-estate integration, supply chain optimization and brand recognition under the interruption of online retail. However, the online retail also reached its maturity state with pure visit volume-based business model. “New retail” is the concept generated under the pressure of the two mentioned points. If we want to define new retail in one sentence, it is the integration of online, offline, technological, data, logistics across the single value chain. As Deborah Weinswig commented, Jack Ma, the founder and chairman of Alibaba believed that this is very much how next-generation commerce will look globally, with large retailers and niche category specialists leveraging technology to provide an integrated service with the consumer at its core.

Retailing_Reinvented_20161118_v2How Alibaba developed the new retail business model?

  • Data-driven mass personalization: Multi-dimensional and large volume customer data reserve helped Alibaba on a higher starting point in the development process. As a consumer of the Tmall.com retail store, I experience a recognizable difference since 2016. Tmall.com recommender system understands me better than myself. com is focusing user activity, engagement and duration of the shopping experience on top of the Gross Merchandise Volume (GMV).
  • The emergence of multichannel and multidimensional competition: Foundation by the mobile payment, the user can be reached both online and offline in almost all shopping circumstances. In addition, Alibaba expanded its territory to many other industries such as finance, entertainment, local service, etc. As such, the company covered the touch point with their customer in a multidimensional way, increased the penetration rate of the brand appearance and ultimately enforced the competitive advantage in the retail industry.
  • Investment in logistic and back-end system: Alibaba is contribution large portion of resources in optimizing the logistic management capability and upgrading back-end system to improve customer experience and diminishing cost at the same time.


As already mentioned in the post “beyond Omnichannel: Alibaba’s “new retail” strategy”, HEMA is the pioneer in the “New Retail” industry. Nevertheless, you can also see that the upfront capital investment for offline store opening is huge. The advantages leading to the economics of scale and capital accumulation is not easy to imitate for start-up companies.

How can START-UPs understand the “New Retail”?

Product (consumer products)

  • Logistics: Traditional furniture industry have a much-dispersed range of brands and products which have no quality standardization in China which makes price comparison almost impossible. For example NetEase.com[1], it partnered with reliable suppliers, optimized logistics and filtered out high cost-quality ratio product.
  • Source of supply: International e-commerce provided differentiated product compare to local suppliers to the consumers no matter import or export goods. RED[2] helped their consumer to explore and purchase product all around the world. On the other side, JollyChic[3] brings Chinese product to the world.

Environment (shopping environment, circumstances, and channel)

Traditional e-commerce is mainly based on the visit volume. The concerns are: “How to purchase visit volume at a low price and sell it at a high price”; “How to convert visit volume into real cash?”

Consumer (target market)

The key is to personalize the shopping experience in order to lock-in the purchasing power.


Look back at 2017, the e-commerce companies in China did many tests. There are also trends emerging such as social commerce, subscription-based business model, multidimensional shopping experience, and personalization. The social commerce business model and service commerce business model is particularly interesting to discuss.

Social commerce

As we discussed in the lecture, proximity influence dominant population influence when proximity influence exists in theory.[4]Word of mouth is the main driver for the emergence of the social commerce business model because it solved three problems for the e-commerce companies: Trust, natural, cheap.

Compare to the social commerce that is crazily popular on Wechat, Facebook already implemented social commerce on their platform but with the less successful story. Wechat compares to Facebook has a unique advantage. Wechat Group, Friends circle, Mini-program covers the entire sight and time of the consumers. Unlike Facebook that pushes customized display advertising to the customer, on Wechat platform the e-commerce store can advertise the product through all kinds of ways. If a customer refused to buy the product, the store could engage themselves in Wechat group. If consumer left the Wechat group, they still have to look at their Friend circle. Even they blocked the Friend circle, there are Mini-programs (which contain gamification concept for advertising). Thus, the consumer will be informed about the product all the time if they still use Wechat.


Service commerce

  • Membership-based model

E-commerce companies will provide a special premium for the members of the company. Amazon Prime is the most successful and well-known example of the membership-based model. Mimic the business model from Prime and implement it in Chinese e-commerce industry is not fully applicable because the companies should provide more localized benefit to their consumer. But figuring out the irresistible, unneglectable benefit for the consumer which trigger them to spread good words is still a long way to go.

  • Subscription-based model

The company can facilitate the consumers to grow a habit, increase the purchase frequency and lock-in purchasing power through a subscription-based model. For example, the flower subscription company facilitate the consumer to grow a habit of having fresh flower around them. Originally, the flower is a low purchasing frequency product. However, if a consumer subscribes weekly delivery of flowers, the purchasing is becoming more predictable with a higher frequency.


In general, social commerce and service commerce collect more customer data by engaging them in a high frequency that allows them to customize shopping experience better. New consumer, new market, new product. Companies can deliver their product and service in a new way. I believe that there will be an opportunity for “New Retail” in both online and offline.






[1] NetEase, Inc. (NASDAQ: NTES) is a leading internet technology company in China. Dedicated to providing online services centered around content, community, communication and commerce, NetEase develops and operates some of China’s most popular PC-client and mobile games, e-commerce businesses, advertising services and e-mail services. In partnership with Blizzard Entertainment, Mojang AB (a Microsoft subsidiary) and other global game developers, NetEase also operates some of the most popular international online games in China.

[2] Red provides its users with a platform to learn about and share shopping tips, deals, and experiences from their trips abroad. Users can browse through lists of the most popular brands for a category, and through products on brands’ exclusive pages. They can share pictures of products they have purchased, displaying them in a Pinterest-like interface with commenting and liking features.

[3] Jollychic.com has a strong bond with industry insiders and collaborates intensively with main stream. We offer the latest fashion ingredients for those interested; We are a partner with dozens of reputable import & export companies, warehousing & logistics companies and after sales service provider from around the world. [https://www.jollychic.com/]

[4] Dewan, S., Ho, Y.-J. (. & Ramaprasad, J., 2017. Popularity or Proximity: Characterizing the Nature of Social Influence in an Online Music Community. Information Systems Research, 28(1), pp. 117-136.


Are Virtual Communities Different From Face-to-Face Communities?

A community has always been seen as a group of people that interact with each other, face-to-face. But since the rise of the digital age, a new phenomenon has occurred; digital communities. This blog post tries to give an overview of the original community and the virtual community and how they differ. The blogpost is based on the article “The Experienced “Sense” of a Virtual Community: Characteristics and Processes” by Blanchard and Markus (2002)

Original communities

Original communities are face-to-face communities. There are two types: geographic neighborhoods, so place-based communities and communities of interest. The communities of interest were groups of people that bonded over interests, rather than the geographical location. So, these types of communities were more widespread. Since the limited use of digital devices and or the internet, most of these communities included face-to-face contact and no such thing as chatting. Not all neighborhoods are also communities.

Virtual community

Virtual communities are built around digital devices using the internet. The people within the community are connected mostly digital. In some cases, they know each other in person and also interact face-to-face. But when it comes to the community as a whole, that is only digital. Like in original communities, there is a difference in virtual settlements and virtual communities. Virtual settlements exist when objective measures of computer-mediated interaction exceed some threshold levels. Not all virtual settlements are virtual communities.

Sense of community

So why don’t all neighborhoods count as communities? In order to really be a community, the concept ‘sense of community’ plays an important role. Without this ‘sense of community’, the group of people is just a group of people.

This phenomenon was found in the original communities, but studies showed that this concept was also applicable in the virtual communities.

The definition used in the article is: ” a characteristic of successful communities distinguished by members’ helping behaviors and members’ emotional attachment to the community and other members.” There are some behavioral processes that contribute to the sense of community, namely: exchanging support, creating identities and making identifications and the production of trust. These are quite the same for both type of communities.

Researchers are still in doubt if the sense of community is the reason for communities to exist, or that it is an effect caused by communities. It is mostly presumed that the sense of community is necessary for a community to exist rather than that it is treated as an effect by communities.

The ‘sense of community’ experienced in virtual communities is called ‘sense of virtual community’. When this is experienced, it is called a virtual community. There are also a number of social processes and behaviors that should be present in these communities, namely: providing support, developing and maintaining norms and boundaries, social control and some more.

Sense of community is not forever existing, it can decay or be extinguished. This can be caused by leaders dropping out or if new members with different values join, etcetera.

Active members vs lurkers.

There are different types of members that are involved in most communities. The active members are mostly the leaders of the community, they contribute a lot to the content and interactions within the community. There are also members that are not as involved but still contribute once in a while. The last type are the lurkers. These members are not active, but only present.

In the study, members believed that the newsgroup they were subscribed to, was a community. But their attachment to the community varied with their participation, and their perceived benefits from participating.

Original communities vs Virtual community: what are the differences and what is the same.

The article argues that because the communities have differences in characteristics, the feelings are a little bit different formulated, but are quite similar in meaning. Table 1 gives an overview of the main feelings experiences with sense of community in the two different types of communities.

Table 1: Comparison of SOC and SOVC

Dimensions of SOC Dimensions of SOVC
Feelings of membership Recognition of members
Feelings of influence Exchange of support
Integration and fulfillment of needs Attachment
Shared emotional connection Obligation
Identity (self) and identification (of others)
Relationship with specific members

So, overall the communities have a similar buildup and similar processes. But some differences exist because of using digital devices versus face-to-face interactions.

What are the benefits for companies?

Companies are creating a virtual meeting place or platform for their customers to interact on. The companies try to get (positive) feedback of their consumers. This method is also used to try to motivate people to buy their products or just get the name of the company or product out there. But this group of people that the companies are putting together in this way, does not make a community. In order to have a community, the sense of community is needed. The feelings of belonging and attachment need to develop. The result of the community is that the value is more than all individual people added together.

A community within an organization will among others effect in an increase in job satisfaction and organizational citizenship behavior-loyalty.

This article shows the potential value of creating communities, for commercial reasons as for organization reasons.

Persuasion in crowdfunding: An elaboration likelihood model of crowdfunding performance

Authors paper: Allison, T. H., Davis, B. C., Webb, J. W., & Short, J.C.

Since 2009, crowdfunding and crowdfunding platforms have experienced a high growth in popularity (Google Trends, 2018). Simultaneously, quite a lot of studies have been conducted on this topic. One finding of those studies was the fact that only 36% of the launched projects succeed in reaching their goal (Courtney, Dutta, & Li, 2017). One potential reason for the failure of the majority of the launched projects, is the lack of convincing information and peripheral cues. Allison et al. (2017) study exactly this in the context of the crowdfunding platform Kickstarter. In addition, they also study how attributes of the funders determine the effect of persuasion.

Using the elaboration likelihood model (ELM) of persuasion, the following questions take a central position in the paper: 1) How can crowdfunding entrepreneurs successfully persuade potential funders to provide capital through the use of issue-relevant information and peripheral cues? And 2) How does the motivation and ability of funders influence the way in which persuasion occurs?


The elaboration likelihood model of persuasion tells us that persuasion happens through two distinct routes: The central route where people evaluate information critically and consciously and the peripheral route where people evaluate the message more affectively based on contextual cues, such as the underlying tone of a given text. In the case of this study about crowdfunding projects, specific concepts are measured to study both routes and their effect on the performance of the crowdfunding campaign. The data for the concepts was collected from 383 crowdfunding projects.

The following concepts represent the evaluation of funders through the central route:

  • The education and experience of the entrepreneur
  • The perceived quality and usefulness of the product

For the peripheral route, the presence of the following cues in the product’s pitch represent the route’s strength:

  • The portrayal of a dream
  • The adoption of a group identity
  • A positive narrative tone throughout the text

In addition, the ability of the funder is measured through their crowdfunding experience (number of funding actions in previous crowdfunding campaigns), and the motivation of the funder is measured through the required funding commitment of the campaign. Commitment was high when someone funded while the lowest-priced reward of a crowdfunding project was above $10, and commitment was low when someone funded while the lowest-priced reward of a project was lower than $10. Both ability and motivation of funders were assumed to moderate the effects of the central route and peripheral route on the crowdfunding performance.



After modeling all the variables, only the positive narrative tone of a campaign text did not have a significant effect on the performance of crowdfunding campaigns. All the other variables, related to the campaign text, characteristics of the product and the entrepreneurs, had a significant impact on the success of the crowdfunding campaign. So if the education or experience of an entrepreneur is high, the crowdfunding campaign is more likely to succeed. Similarly, the success of the campaign is positively related to the product quality or usefulness. Lastly, if peripheral cues like the portrayal of a dream and the adoption of a group identity is used in the text, the crowdfunding performance is likely to be higher.

The strength and likelihood of these effects is increased when the motivation and ability of the funder are high, which was validated within an experimental setting in a second study.


The primary strengths of this paper relate to the hypothesis development and the study approach. Because so many crowdfunding campaigns fail, it is very good to know about practical approaches that attract more funds. This is exactly what the authors study in this paper. Combining a classic model with emerging businesses provide very useful insights for the field. Related to this strength of the paper, the approach of the authors in hypothesizing is also very good. They develop hypothesis fully based on the theory and past studies, to increase the robustness of their potential findings and to really add value to the academic field as well. Lastly, another strength is the second study that was conducted, that used participants, surveys and an experimental setting. This increases the validity of their findings, as the first study only used scraped data from Kickstarter to model the outcomes.


Next to the strengths, the paper also has its weaknesses. The most obvious, yet most impactful, weakness is the lack of generalizability due to the data from only one crowdfunding platform. While Kickstarter is one of the biggest crowdfunding platforms, the 383 selected projects and their funding could differ from other platforms in terms of guidelines, funding mechanisms and interface. If other platforms were considered as well, the specifically studied cues could have different forms and consequently, results, than Kickstarter.

A second weakness is potentially influencing the general results of the study. In a crowdfunding platform like Kickstarter, projects can experience unusually high performance when they get featured on a ‘trending’ or ‘what’s hot’ page, as well as when they receive a lot of external  media attention. The authors of this paper have not measured or controlled for these events. Out of 383 projects is it quite likely that one or more of them have received more funding because they were featured on a specific page or news medium. Uncontrolled variables like this cause a decreased causality of the hypotheses, because a couple of these projects with similar entrepreneur education (for instance) could easily skew the results in a way that it reaches significance, while this was not the case if one or two of these projects were dropped  (Type I error). Therefore, the authors should have included more controlling variables that had an impact on the project’s performance.



Allison, T. H., Davis, B. C., Webb, J. W., & Short, J. C. (2017). Persuasion in crowdfunding: An elaboration likelihood model of crowdfunding performance. Journal of Business Venturing32(6), 707-725.

Courtney, C., Dutta, S., & Li, Y. (2017). Resolving information asymmetry: Signaling, endorsement, and crowdfunding success. Entrepreneurship Theory and Practice41(2), 265-290.

Crowdfunding. (2018). Google Trends. Retrieved 9 March 2018, from https://trends.google.nl/trends/explore?date=all&q=crowdfunding

 Written by Bart – 383128

Each can help or hurt: Word of mouth influence in social network brand communities

Do you remember earlier this year when an infamous Swedish fashion company was very passionately and publicly criticized for a photograph including an afro American child and a sweater with an admittedly very controversial logo? This major PR fail lastly even lead to physical aggression in one of the brand’s stores in South Africa, but is only one of many recent examples where customers make use of their viral online voice (don’t get me started on German car manufacturers).

But what about you, do you follow your favorite brands on Instagram and Facebook? Do you maybe secretly bash or boost them yourself?

Power to the (online) people

Researchers have now found new insights into how negative or positive opinions of others influence our own behavior in such social network brand communities (fancy language for Facebook & Instagram page) and how this relationship is affected by the goal instrumentality of the community itself. Goal what? I knooow, but it actually sounds more complicated than it is – if you’re for example someone looking for like-minded people crushing on the newest Gucci coup (Drones on the runway, hello!) you pursue a different goal when clicking the heart and like buttons (what they call social-goal community) than someone wanting insight into the intuitiveness of the new Google Pixel’s menu (functional-goal community). Makes sense, right? So basically, goal instrumentality just means whether or not you find what you’re looking for on those  pages.

They found that both bashing and boosting have more severe implications if you’re more the Gucci type, meaning that opinions of fellow admirers will most likely enhance your own activity within the community (gimme those likes), whilst reading some douche bag hater comment is likely to kill the mood (get me outta here!). This is related to this notorious goal instrumentality – if your goal is to share those googly eyes then obviously other worshippers will help you reach that goal more than some questions about your fav brand’s sourcing choices (although maybe legit). If you do happen to stumble across some idiot who dares to disagree with your passion, consumers in those social-goal communities tend to have more negative reactions (First of all, ?!#*§) – I mean you gotta fight for what you love, right. And they need research for that, I know.

lacoste insta


If you’re however more the Pixel type (not judging, you wanna know what you pay those franklins for), some sassy statements may just be what you’re looking for – after all it can’t ALL be puppies and kittens and if you feel like pure glorification, might as well watch the newest marketing spot.

Okay, cool. And?

And why am I telling you this? First of all, you can fill the awkward silence when the small talk is over with the annoying colleague who just made partner sounding super sophisticated (who’s the star now?). And second, if you stumble across a second Gucci Facebook page for functional info only, you’ll know why. Or even better, if you work in digital you can shine in the next weekly meeting à la “You know, bad reviews are actually not always bad for us – maybe we just need a clear separation between social-goal and functional-goal communities and communicate this purpose to increase the customer’s goal instrumentality.”. Can you imagine your boss’ face?

In either way, it’s also shown now that deleting negative comments cannot be the solution – it decreases credibility considerably and can even harm your goal fulfillment. Take this, social media teams and let us rant (but also drool) in peace.

Nobody’s perfect

But despite these interesting insights, there’s also a few points those researchers didn’t think of – what if I for example, don’t follow a specific goal in hitting the ‘Like’ button and just want to be sure to always have the latest news and hottest content about new collections and collaborations (or maybe even surprise discounts)? Is this really a functional goal? And also, assuming that I follow a social goal of approval by my fellow brand admirers – what if we all agree that the latest collection was more toss than take, like in the picture below? It happens to the best. Isn’t the bashing then also part of my goal fulfillment if everyone agrees?

LV insta

For next time…

Maybe it would be helpful to further distinguish between certain types within these communities – hardcore fans who actually read through the comments and are ready to defend their fav brand come what may, “normal” people who mostly want to be up to date and enjoy content, but will not start a fight over the label to defend their passion and more passive users who hit the thumbs up ages ago, but are not really attached to the brand. Also concerning the studied industry a bit more variety would be interesting, since all of the four studies were treating an automotive context. Whilst I love fast cars myself, this is still a quite specific context and it would be interesting to see if the results hold up for other contexts such as fashion, lifestyle or tech brands.



Relling, M., Schnittka, O., Sattler, H., & Johnen, M. (2016). Each can help or hurt: Negative and positive word of mouth in social network brand communities. International Journal of Research in Marketing, 33(1), 42–58.

How Trending Status and Online Ratings Affect Prices of Homogeneous Products

The Internet and Word-of-Mouth (WOM)

Ever since the inception of the Internet, consumers have benefited from extensive opportunities to share their evaluations of products online. Most e-commerce platforms allow consumers to review products, and an increasing number of opinion platforms have been introduced that offer online consumer ratings and reviews. Furthermore, most online retailers are now listing and selling trending products, defined as products that large groups of individuals are currently purchasing or discussing (Kocas and Akkan, 2016). In their article “How trending status and online ratings affect prices of homogeneous products”, Kocas and Akkan explore the pricing implications of these reviews and trending status. The following research questions result:

RQ1: How do standardised average prices vary with product popularity (measured by the trending status)? 

RQ2: When controlled for popularity, how do standardized average prices vary with average consumer ratings?

Related Theory

Research in marketing and economics have shown that it is profitable for retailers to sell popular products at a discount as advertising the low price is an effective and cheap method to inform consumers of the extra surplus they could get by purchasing these products (Elberse, 2008). In the present study, trending is considered an indicator of product popularity as well as a costless form of advertising – trending products signal desirability and potential positive surplus to consumers (Hosken and Reiffen, 2004). Hence, one can assume that trending products are priced lower by retailers, as the resulting increase in demand more than likely compensates for the decrease in marginal revenue per item sold.

Furthermore, several studies have shown that positive ratings and reviews have a positive effect on sales (Baek et al., 2012). Similarly to trending status, high ratings can act as a signal of desirability. Hence one can reasonably assume that highly rated products should be priced lower by retailer for the same reason as aforementioned.

Formally stated,

H1: Retailers randomize prices of products independently. The average and minimum profit-maximizing prices for the trending products are lower than the prices for non-trending products given identical average consumer ratings.

H2: The average and minimum profit-maximizing prices for the product with higher average consumer ratings are lower than the product with lower average consumer ratings given identical trending status.


This study analyses data gathered from 24 of the 28 categories of books available on Amazon.com from May 25 to September 13, 2011 and includes a sample of 466’190 books. Both hypotheses are supported by the experiment, showing that a trending product should be priced lower than other products in order to exploit the higher number of browsers these trending items attract. Similarly, highly rated products lead to a higher conversion rate (from browsing to purchasing) and, hence deserve lower prices.

Strengths & Weaknesses

5-stars-no-padding Whereas several studies have examined the impact of viral characteristics of products on consumer behaviour and pricing policies, this study is the first to empirically examine the influence of trending status on pricing online in a field experiment with a large dataset. Similarly, whereas several studies have examined the impact of online reviews on consumer behaviour, no prior work has examined how online reviews and ratings affect prices of homogeneous goods. A strong point of this paper is that it acts on these 2 gaps to provide novel findings, and tangible and actionable insights to practitioners.

5-stars-no-padding  Another strength is that this paper provides a detailed methodology, which is complemented by an appendix as well as a detailed explanation of the economic foundations behind the theory (including formulas). This level of details increases the academic relevance of the paper, and allows other researcher to easily replicate the experiments, hence facilitating continuous research on the topic.

1 star    One of the weaknesses of this study is the fact that it only examines one type of products – books. Several studies (e.g. Abdullah-Al-Mamun and Robel, 2014) have shown that price sensitivity varies from one product category to another. Similarly, product reviews are generally more important for certain types of products than others. For instance, for a product such as a microwave, personal taste doesn’t really matter, hence one could expect product reviews to be more important as it provides an objective evaluation. However, for a product such as a science-fiction book, personal taste is important, hence the influence of product reviews is likely lower. Thus, it would be beneficial to replicate this study while taking into account category- and product-specific features as a predictor of prices. This can easily be done by replicating the experiment with more product categories on Amazon, and would validate the robustness of this study’s findings across product categories.

1 star    A second weakness of this paper is the fact that it examines the impact of online ratings by relying only on single-dimensional rating schemes. Online platforms display reviews using a variety of formats, and many platforms provide separate ratings for different product attributes. Research has shown that multi-dimensional and single-dimensional rating schemes in online review platforms have different impact on consumers (Tunc et al., 2017). Similarly, this study only looks at the ratings but not at the content of the review. However, studies have shown that the latter can influence consumer behaviour. Both these factors can influence the conversion rate from browser to buyer (Mudambi and Schuff, 2010) and thus the profitability of retailers. Hence, it would be interesting to replicate the present research in the context of multi-dimensional rating schemes, and take into account the actual content of online reviews.


We have seen that there are significant advantages to demand-based pricing for popular products with a relatively high market share. Hence, online retailers should monitor signs of trending as they act as a positive desirability signal that increases the demand of price-comparing consumers. By responding to trending signs and adjusting their prices, retailers can optimise their profits. Nevertheless, managers should be cautious of the research findings and conduct further experiments when applying them to products other than books. Finally, managers should be careful about the pace at which they adjust their prices – popularity status can change extremely quickly, but consumers will not react well to frequent price changes.


Abdullah-Al-Mamun, M. K. R., & Robel, S. D. (2014). A Critical Review of Consumers’ Sensitivity to Price: Managerial and Theoretical Issues. Journal of International Business and Economics, 2(2), 01-09.

Baek, H., Ahn, J., & Choi, Y. (2012). Helpfulness of online consumer reviews: Readers’ objectives and review cues. International Journal of Electronic Commerce, 17(2), 99-126.

Brynjolfsson, E., Hu, Y., & Smith, M. D. (2010). Research commentary—long tails vs. superstars: The effect of information technology on product variety and sales concentration patterns. Information Systems Research, 21(4), 736-747.

Elberse, A. (2008). Should you invest in the long tail?. Harvard business review, 86(7/8), 88.

Hosken, D., & Reiffen, D. (2004). How retailers determine which products should go on sale: Evidence from store-level data. Journal of Consumer Policy, 27(2), 141-177.

Kocas, C., & Akkan, C. (2016). How Trending Status and Online Ratings Affect Prices of Homogeneous Products. International Journal of Electronic Commerce, 20(3), 384-407.

Mudambi, S. M., & Schuff, D. (2010). Research note: What makes a helpful online review? A study of customer reviews on Amazon. com. MIS quarterly, 185-200.

Tunc, M. M., Cavusoglu, H., & Raghunathan, S. (2017). Single-Dimensional Versus Multi-Dimensional Product Ratings in Online Marketplaces.

Music is your business

Always dreamed of being one of the coaches of The Voice or X Factor, but your lack of musical talent is the thing keeping you from this? Or have you tried breaking through in the music industry, but has your beautiful voice not yet hit the masses? In that case the platform ‘My Major Company’ will enrich your life. This platform gives everyone the opportunity to help an artist produce his or her album, eventually resulting in the artists being able to break through in the music industry.


How does it work?

My Major Company involves consumers in the selection and the eventual success of new and upcoming artists, since 2007 and reached their peak of contributors in 2010. The website portrays an increasing amount of musicians, containing detailed information about their music and themselves. (Ple et al., 2010) Moreover, consumers can listen to work of musicians, help them with funding and comment on their songs with strategic decisions, development or appreciation. This makes this customer-integrated business model a combination between a community driven business model and a crowdfunding business model. When a project is funded enough the albums will be produced, distributed and advertised, which can be a dream come true for many artists. As the winning amount an artist received from backers was €150.000, which can be seen in the following figure.

Screen Shot 2018-03-08 at 16.18.50Figure 1: Lay-out for online platform ‘My Major Company’ (MyMajorCompany, n.d.)

Crowdfunding business model

Using crowdfunding as business model reduces the importance of traditional geographic constraints for consumers, but gives access to funds and avoidance of financial risk to the musicians. (Mollick, 2013; Matinez-Canas et al., 2012) Moreover, for musicians this is positive because pooling contributions of crowdfunders, and thus redistributing risk, opens up possibilities to release records that would else have never been published. In return backers in the platform will be paid 30% of the net income generated by artists they funded. (Ple et al., 2010) However it has been studied that there ought to be a significant amount of backers, making repeated contributions in order to make the crowdfunding campaign a succes (Galuszka et al., 2014). However, there will always be the disadvantage that rivals will be able to copy ideas developed on the platform (Ple et al., 2010).


Online community business model

Having a community on a crowdfunding platform can be very beneficial as this encourages new customers to join, increases quantity and eventually the quality of the product offering (Ple et al., 2010). This shows that not only the financial aspects are vital, but also the social network ties between potential backers and the musicians in this business model have been shown to be extremely important in crowdfunding business models (Agrawal et al., 2012; Galuzka, 2014). Mollick (2013) adds to this the dynamics of success and failure lies in personal networks and project quality. Finally, this business model gives the opportunity in an early stage to identify the actual target audience, for instance the songs people listen to within this business model (Matinez-Canas et al., 2012). Nonetheless, it is found that 75% deliver products (in this case albums) later than expected by the backers (Mollick, 2013). Therefore it is of great importance that founders will be encouraged to set appropriate goals and careful planning. Moreover, outsourcing the firms’ control can be negative due to non-relevance posted within the communities such as spam (Tsekouras, 2018). This might be problematic for firms, as this might not comply with the institutional arrangements set.


Produce the new artists you like!

The combination of a crowdfunding and online community business model has proven to be very beneficial for companies, however, for backers this can be of high potential too. Its value proposition lies in of making music your business concerns a broad amount of stakeholders interested in the music industry. By having a say in what music will be produced and helping musicians by funding the and giving them advise, backers’ perception of the music industry will change completely. For just €10,- it is possible to help an artist break through in the music industry. However, bear in mind that it is not possible to buy more than 100 shares of the same artist. (Ple, 2010) Even though this business model has not expanded their business in the last years, in my opinion, this business model was a pioneer of communities and crowdfunding in the music industry and should therefore not be forgotten.




Agrawal, A., Catalini, C. and Goldfarb, A. (2014). Some Simple Economics of Crowdfunding. Innovation Policy and the Economy, 14(1), pp.63-97.

Galuszka, P. and Bystrov, V. (2014). Crowdfunding: A Case Study of a New Model of Financing Music Production. Journal of Internet Commerce, 13(3-4), pp.233-252.

Martinez-Canas, R., Ruiz-Palomino, P. and Pozo-Rubio, R. (2012). Crowdfunding And Social Networks In The Music Industry: Implications For Entrepreneurship. International Business & Economics Research Journal (IBER), 11(13), p.1471.

Mollick, E. (2014). The Dynamics of Crowdfunding: An exploratory study. Journal of Business Venturing, 29(1), pp.1-16.

MyMajorCompany. (n.d.). MyMajorCompany – Tous les projets à financer. [online] Available at: https://www.mymajorcompany.com/projects [Accessed 8 Mar. 2018].

PLÉ, L., Lecocq, X. and ANGOT, J. (2010). Customer-Integrated Business Models: A Theoretical Framework. M@n@gement, 13(4), p.226.

Tsekouras, D. (2018). CUSTOMER CENTRIC DIGITAL COMMERCE – Session 6.