Category Archives: Articles

Share products you love

Imagine it’s July 2017 and you’re a freshly graduated BIM student. Together with a friend you decide to start your own company and sell your own products. You have some great ideas and great plans! Everything is elaborated in your business plan and you are ready to enter the market. But how are you going to reach your customer? Making use of social media would make sense, since almost 10 million people in the Netherlands visited Facebook (marketingfacts, 2017). How can you use these social media platforms in the most effective way? This is where Sellify comes along!

Sellify. What is it?
The name Sellify comes from sell, satisfy and amplify. “These words stand exactly where our products stand for.”, says CEO and co-founder Lennert Pieters. Sellify is the first crowdselling platform in the Netherlands, what makes Sellify very unique, but what is it exactly?

“With Sellify you can help entrepreneurs reach more customers by sharing the products that you love on your social media. Simply share a product with your friends in order to offer them an exclusive discount and, in addition, you will make a commission on each sale! It’s a win-win situation. You can choose for yourself which of the offered products you like and want to share.” (

As a “influencer” you support other products by sharing them on your social media.

What is it?

Their mission is to make e-commerce accessible and reachable for everyone by offering a full service of distribution, delivery and payment within 60 seconds. “No cure, no pay”, is what they say.  At first place, the platform was initiated for consumers, small entrepreneurs and retailers, but more and more organizations made use of the platform. That is one of the reasons they switched their business model to only B2B.

Take a look at this video to get a better impression of their platform. How does Sellify work?

How does it work?
You and your friend decide to make use of Sellify. What now?

Sellify places your products online and makes sure of a tremendous reach by making use of influencers in their own network. They ask them to share your product on different social media channels, like Facebook. These social influencers exactly know who their friends and followers are, so they also know whether they will like to buy your product or not. When an influencer decides to share your product on her Facebook-profile, their friends and followers can buy your product with a 10% discount. As a bonus, the influencer gets 10% of the selling price of your product.

How does it work.png

Sellify makes use of a cost-per-sale model where the entrepreneur only pays if he or she has sold something. With each sell, Sellify holds on to a minimum of 25% on the selling price, but this money is divided over the seller, influencer and Sellify. Eventually, Sellify will get 5% of the selling price.

So Sellify made a great unique platform, but what now?
Sellify makes use of the social media platform Facebook and Twitter. For the future, they want to add more social media channels, such as Instagram and LinkedIn. Another subject they want to address is to reach a higher conversion by creating a better fit between products and social-media influencers. To reach this goal, Sellify asks the influencers a couple of questions about their interests and are expanding their influencers database.

What do you think?
Many studies showed that when a product gets recommended by a friend or social influencers, the effect of buying this product is much greater than when a company itself tries to promote this product. Customers believe their friends more than the message told by a company. This is one of the reasons why this idea might work. But on the other hand, there are already so many ways on social media to get the customers more involvement and more engaged. There is already so many promoted and shared content on Facebook.. Will this idea be differentiated enough to make a difference? What do you think? Do you think this new business idea might pull it of?


To Keep Or Not To Keep: Effects of Online Customer Reviews on Product Returns

By Madeleine van Spaendonck (365543ms)

In the US, the current average return rate for products bought online is approximately around 30% of purchases (The Economist, 2013). Most returns take place due to customers’ negative post-purchase product evaluation rather than product defects. One factor that is found to have an impact on this is the role of Online Consumer Reviews.

This is what Minnema et al. (2016) investigated in their study “To Keep or Not to Keep: Effects of Online Customer Reviews on Product Returns”. It uses a multi-year (2011-2013) dataset from a European online retailer that offers both electronics and furniture products. The paper examines the impact of three OCR characteristics (valence, volume and variance) on return decisions (figure 1). The researchers evaluate the net effect of OCRs, looking at its influence on both purchase and return decisions.

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The hypotheses examined are based on the ‘expectation disconfirmation mechanism’. Post-purchase satisfaction results from the combination of customer expectations formed at the purchase-moment, product performance, and the difference between them. Negative expectation disconfirmation therefore decreases satisfaction, leading to a higher return probability. Therefore, higher expectation levels should lead to higher purchase and return probabilities, while higher expectation uncertainty should lower these.

Main results

Figure 2 presents a summary of the results of the study.

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A particularly counterintuitive insight is that overly positive review valence (whereby the current OCR valence is higher than the long-term product average) leads to not only more sales but also a higher return probability. A potential reason for this is that OCRs induce the customer to form product expectations at the moment of purchase, leading to higher purchase probability. However, high expectations due to overly positive reviews may not be met. This leads to negative expectation confirmation, which then leads to higher return probability. Review volume and variance mostly affect purchase decisions, having little to no effect on product returns.

Strengths, Weaknesses and Suggested Improvements

While the majority of scholarly work in this field focuses on OCRs effects on product sales, this paper also addresses the lack of understanding of its effects on product returns. Taking into account both aspects is vital, because the prediction of OCR effects on retailer performance may be overly optimistic or pessimistic if only its effects on sales are considered. The study also shows that OCR effects advance beyond the moment of purchase and have the power to affect the decision to return a product. However, the model did not incorporate other information sources available at the purchase-moment that affect return-likelihood, such as product descriptions and pictures provided by the retailer. A comparative analysis could be used to evaluate whether reviews or retailer-provided information have the strongest impact on returns.

Managerial Implications

The study highlights the importance of considering product returns when evaluating OCR effects, as overly positive reviews may have negative consequences for retailers’ financial performance. Overly positive reviews, leading to more product returns, result in large reverse logistics costs. To reduce negative expectation disconfirmation, retailers should provide information and tools (besides OCRs) that allow consumers to set the right expectations and see if the product really meets their needs.


Minnema, A., Bijmolt, T.H.A., Gensler, S., Wiesel, T. (2016). “To Keep or Not to Keep: Effects of Online Customer Reviews on Product Returns.” Journal of Retailing, 92(3), pp. 253–267.

The Economist. (2013). Return to Santa. December 21, (latest accessed March 8, 2017), commerce-firms-have-hard-core-costly-impossible-please-customers- return-santa

Source for cover photo:

Ministry Ideaz, (2016), How do I return a product I no longer want? [ONLINE]. Available at: [Accessed 8 March 2017].

Culture, Conformity and Emotional Suppression in Online Reviews

Paper: “Culture, Conformity and Emotional Suppression in Online Reviews” by Hong et al., 2016

“While Americans say, “the squeaky wheel gets the grease,” the Japanese say, “the nail that stands out gets pounded down.”

In other words, in the States, people who complain the loudest get the most attention while in Japan, people are discouraged to express personal opinions loudly especially if they don’t fit the community expectations. This phenomenon illustrates the differences between individualist (American) and collectivist (Japanese) cultures as defined by Hofstede (2001) and House et al. (2004). But this post is not entirely about cultural differences – it is about their influence on online reviews. Continue reading Culture, Conformity and Emotional Suppression in Online Reviews

Why users contribute knowledge to online communities: An empirical study of an online social Q&A community

Knowledge & the Internet

Ever since the inception of the Internet, the volume of knowledge has exceptionally increased, especially since it improve-knowledge-managementfacilitates crowdsourcing knowledge. Websites such as Wikipedia and Quora help individuals provide other individuals with information and answers to lingering questions. Quality control is also crowd controlled, where different kinds of voting systems enable fellow users to assess the provided answers and filtering out low-quality ones. Online Q&A communities are special social networks focused specifically on information sharing. They are a special place since there is usually no monetary incentive to motivate people to contribute. This paper focusses on these online communities and tries to explain the motivation behind the contributors.

Related Theory

There are 3 theories that are related to this study and on which the hypotheses are built, they are social cognitive theory, social capital & social exchange theory. The Social cognitive theory claims that that people’s thinking and actions are influenced by watching others through social interactions (Anderson, Winett, & Wojcik, 2007). The theory has been used to analyze how content is generated by users and how this content affects future contributions. Social capital is a known concept describing the value derived from interpersonal relationships and is built over time. It includes trust, respect & friendship among other things (M.M., 2005). The social exchange theory highlights intrinsic rewards from social interactions, similar to economic exchange theory it claims that individuals will behave in a certain way to acquire rewards from an interaction (Liu & Chen, 2005).

What is measured and how?

Based on the previously mentioned theories/concepts 4 aspects were identified that are possible drivers of knowledge contribution in online Q&A communities.

Identity Communication

Identity communication refers to an identityindividual’s efforts to express and present his/her identity. It explains who a person is and how he/she is different from others. It includes the concept of self-presentation information; the transfer of personal information about one’s personality, experience etc. so others understand their social identity (Tajfel & Turner, 1979). In the study, it is measured as a number of items that a user discloses about himself with a maximum of 11 (maximum of items available on the website).

H1: Individuals who disclose more self-presentation information will contribute more knowledge to online social Q&A communities.

Peer Recognition

The more knowledge becomes available the more attention is divided between different sources of information. The same goes for the information in online Q&A communities. Peer recognition is the positive feedback users receive on their behavior and is measured by the number of usefulness votes on a post.

H2: Individuals who receive more positive feedback will contribute more knowledge to online social Q&A communities.

Group-size Effects

Since most intrinsic rewards are based on transactions with others, as explained before, the presence of others and the number of possible recipients are important. A larger following means a wider reach and thus more social rewards (Nahapiet & Ghoshal, 1998). A member’s following is measures by the member’s so-called ‘followers’.

H3: Individuals with a larger group size will contribute more knowledge to online social Q&A communities.

Social Learning

Social learning is a type of learning that comes from observation of others. In online communities content feeds provide constant updates of other individuals actions, providing continuous learning opportunities (Anderson, Winett, & Wojcik, 2007). Social learning is measured by the number of topics, questions and members a participant is subscribed to, the more they are subscribed to the more learning opportunities a member has.

H4: Individuals with more social learning opportunities will contribute more knowledge to online social Q&A communities



The researchers have analyzed 1.762 data points from 306 members of a popular online Chinese Q&A community. These data points include all knowledge contribution behavior from March 15 to June 22, 2014. After processing the data H1, H2 & H4 are supported and H3 is rejected.

Why is this important?

The internet is a great tool to share knowledge, people from all over the world can distribute information to others. This can help people with a more difficult start in life acquire knowledge to help them further. Understanding why people contribute to online knowledge sharing can help increase knowledge that is available online.


Anderson, E., Winett, R., & Wojcik, J. (2007). Self-regulation, self-efficacy, outcome expectations, and social support: Social cognitive theory and nutrition behavior. Annals Of Behavioral Medicine34(3), 304-312.

Anderson, E., Winett, R., & Wojcik, J. (2007). Self-regulation, self-efficacy, outcome expectations, and social support: Social cognitive theory and nutrition behavior. Annals Of Behavioral Medicine34(3), 304-312.

Jin, J., Li, Y., Zhong, X., & Zhai, L. (2015). Why users contribute knowledge to online communities: An empirical study of an online social Q&A community. Information & Management52(7), 840-849.

Liu, C. & Chen, S. (2005). Determinants of knowledge sharing of e-learners. International Journal Of Innovation And Learning2(4), 434.

M.M., W. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly: Management Information Systems29(1), 35-57.

Nahapiet, J. & Ghoshal, S. (1998). Social Capital, Intellectual Capital, and the Organizational Advantage. The Academy Of Management Review23(2), 242.

What’s your recommended size?

Shopping online is more convenient, however it becomes tricky when shopping for clothes as we’re not able to try the clothes on. Hence, we purchase items in the size we think fits us best. This, unfortunately, may not always work in our favour. Often, we receive an item that doesn’t fit us well. We then either return it, store it at the back of our closets hoping one day it will fit, or give it to a friend. Essentially, a waste of time and money.

ASOS, a large online fashion retailer, just launched a new recommendation tool that helps solve this problem for their shoppers.

What is it?

The new tool provides customers with a personalized recommendation of a size it thinks will fit them best. It suggests a size based on customers’ past purchases and returns. Here’s how it works (Cherrington 2017):

  1. A recommended size instantly appears when the customer views an item.1
  2. Clicking the link shows the customer what the recommendation is based on.2
  3. Customers also have the option to provide input to improve recommendation accuracy by: (1) selecting which past purchases didn’t fit, (2) adding height, weight, age, and desired fit type (very tight to very loose), (3) selecting tummy shape, hip shape and bra size.

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If a customer is new, they can add in their height and weight and discover which size similar customers purchased and did not return.

ASOS has received a backlash for introducing this new tool. Some women have taken to Twitter to vent their frustrations that the tool is insulting and inaccurate. (Cherrington 2017)


Others have responded more positively to the new tool, as customers no longer have to guess which size would fit and it saves the time and effort that would have been spent on returns and exchanges. It not only provides a personalized recommendation to customers, but it also includes the input of customers to produce better results, making customers feel like they are part of the creation process.

ASOS’ business model is to provide their customers with engaging content and experiences, great fashion at a great price and excellent service through an “effortless online and mobile shopping experience”. (ASOS 2017) More than just a fashion retailer, ASOS prides itself as a technology company – constantly innovating to improve service and customer experience. This new recommendation tool is a strong reflection of their business model and values.

Efficiency Criteria

The joint profitability criteria is met as this recommendation tool improves the joint value for both ASOS and its customers. While some customers are currently unhappy with this new tool, once ASOS improves the system to deliver more accurate recommendations, customers are likely to appreciate the tool more. It saves them from spending money on clothes that don’t fit and will increase customer satisfaction.

The investment cost of this new recommendation tool is low as the company only needs to improve the recommendation system based on feedback. The company also benefits from the increased customer satisfaction and sales from customers that previously abandoned their shopping cart due to size concerns.

The feasibility of the required allocations is also met. The polity and judiciary dimensions of the institutional environment do not relate directly, however the social norms dimension is met as ASOS has a strong reputable brand,  thus creating trust with customers.


ASOS 2017, ASOS Story, ASOS Plc, viewed 9 March 2017, <;.

Cherrington, R 2017, ‘ASOS Is Guessing What Size Its Customers Are, And They’re Not Happy About It’, The Huffington Post, 24 January, viewed 9 March 2017, <;.




How Brand’s User Base Visibility in Social Media Platforms Effect Consumer’s Brand Evaluation

Social media is a widely used channel for companies to connect with consumers. Approximately 83% of Fortune 500 companies have used some form of social media by 2011 (Naylor et al., 2012), which have increased even more by now. Many consumers use these social media platforms to get deeper knowledge about a brand and who affiliates with it. This is useful because consumers reaction to a brand may be affected if they know who other users are (Bearden, Netemeyer, and Teel, 1989; Berger and Heath, 2007). Via these platforms, consumers have the possibility to see other people who affiliated with the brand. This passive exposure to a brand’s supporters is identified as ‘mere virtual presence’ (MVP). This research tries to answer what the effect are of the different types of MVP on brand evaluation and purchase intentions, as there is still little know about the subject.

Consumers find more affinity with a certain brand if they see that similar others support the brand (Berger and Heath, 2007; Escales and Bettman, 2003). Because of this, it is expected that individuals who deal with similar MVP with the brand’s user base will experience high levels of inferred commonality. Therefore, they positively evaluate the brand. On the contrary, if the consumer experience a dissimilar MVP, they will evaluate the brand downwards. Another research suggests that when there is no information available about others, consumers anchor on the self and assume that those others are like them (Naylor, Lamberton, and Norton, 2011). Thus, probably a more safe decision is not displaying pictures of others at all, which is called ambiguous MVP. This ambiguous MVP results in that consumers will project their own characteristics on the brand’s user base, hence higher affinity with the brand. However, a brand’s user base cannot be completely similar to a consumer and is more heterogeneous. Therefore, the last form of MVP this research investigate is that consumers evaluate a brand more positively if they are confronted with a small proportion of similar individuals in a large heterogeneous group.

Findings from this study have the following implications for positive brand evaluations: (1) If the brand’s user base is homogeneous and similar to the target audience, reveal their identity. (2) Second, if the brand’s user base is heterogeneous, but includes users who are similar to the target audience, also reveal their identity. (3) However, maintain ambiguous MVP if the brand’s user base is dissimilar from the target audience. This will result in that consumers evaluate the brand the same as in the similar MVP context. (4) Lastly, results indicate that when brands are jointly evaluated with other brands similar MVP yields better performance than ambiguous MVP. This positive brand evaluation consequently results in higher purchase intentions.

This study contributes to the literature how firms can best manage their social networks in meeting strategic objectives and enhance their brand evaluation. Moreover, this research help to guide brand managers when it is useful to reveal the identity of their online supporters or to remain an ambiguous MVP. Thus, managers are informed which social media platform they should choose because some control over specific fan base is necessary (similar consumers in heterogeneous population). These results are furthermore most useful for new brands to establish a larger supporter’s base. And to manipulate MVP and find similar consumers, firms can target consumers based on demographics. For example, Facebook displays advertisements mostly to certain demographic groups, thus emerging tracking and targeting tools can be used to do this.  Because of this tracking marketers know where their new supporters came from so that they can adjust their MVP and target consumers that fit this demographic profile. This will help brand managers to decide whether to display the brand’s user base or remain ambiguous.


Bearden, W.O., Netemeyer, R.G. and Teel, J.E. (1989) ‘Measurement of Consumer Susceptibility to Interpersonal Influence’, Journal of Consumer Research, 15: pp. 473-481.

Berger, J. and Heath, C. (2007) ‘Where Consumers Diverge from Others: Identity Signalling and Product Domains’, Journal of Personality and Social Psychology, 95: pp. 593-607.

Escales, J.E. and Bettman, J.R. (2003) ‘You Are What They Eat: The Influence of Reference Groups on Consumers’ Connection to Brands’, Journal of Consumer Psychology, 13, 3: pp. 339-348.

Naylor, R.W., Lamberton, C.P. and Norton, D.A. (2011) ‘Seeing Ourselves in Others: Reviewer Ambiguity, Egocentric Anchoring, and Persuasion’, Journal of Marketing Research, 48, 6: pp. 617-631.

Naylor, R.W. Lamberton, C.P. and Norton, D.A. (2012) ‘Beyond the “Like” Button: The Impact of Mere Virtual Presence on Brand Evaluations and Purchase Intentions in Social Media Settings’, Journal of Marketing, 76, 11: pp. 105-120.


Making an internet celebrity-the economy behind it

For most of us, Instagram is not only a way to share and post filtered photos of important subjects of our life like Sushi ate for dinner, friends’ cute cats and dogs as well as selfies, but also a procrastination tool to enjoy the eye candies from internet celebrities, i.e. posted pictures, meanwhile some are making real cash out of their influential photos. In case you are curious on how to make money like an internet celebrity, hope the following tutorial can help and it all comes down to a combination of product placement, endorsement and followers who gradually become consumers as well, since they are the target market of the internet celebrities they follow.

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Law 1: Instagram Endorsement

According to Forbes Magazine, Kylie Jenner who ranks the second on 2016’s Top-Earning’s Reality Stars list, earned $18million in 2016 (Robehmed, 2016). Among which, nearly 20% of the income came from endorsements on social media for promoting other brands’ products. She shilled for at least eight different brands through her Instagram page. It is said to have your product shown on her Instagram, each picture charges at least $300,000 (Lester, 2016), due to the fact that these internet celebrities have considerable audience to broadcast to and easily gather at least one million “likes” on Instagram. The actual advertising effect is also surprising. The year before a noteless make-up brand (Nip Fab) reached out to Kylie Jenner with a hefty bonus. Now that brand is gaining its popularity with a boost from her Instagram endorsement, the market value of the company has reached $100 million (Lankston,2015).

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Another example is from Selene Gomez who sits on 110 million followers on Instagram. Last year she broke a record of asking $500,000 for an endorsing photo from Coca-Cola. The picture is such a huge success that harvest of 6.5 million “likes” on Instagram immediately, which became the most “liked” Instagram in history.Screen Shot 2017-03-10 at 17.55.06

Law 2: Dress with product placement

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Kendall Jenner, sister of Kylie Jenner, who also attracts almost 76 million followers on Instagram, was spotted wearing a certain brand clothes for a long time when appearing in front of paparazzi or casually shot off pictures with the brand’s clothes on and posted on Instagram. While she was paid to by this newly set-up, yet no-fame Australian brand. Most importantly, sales revenue of the brand rocketed thanks to her implied efforts. Consequently, by partnering with Instagram influencers that have thousands or even millions of followers, brands can reach loads of consumers with a single post. Nowadays, many marketing agencies have turned to devote to pairing Instagram accounts that have sizable followers with companies looking for advertising or exposure aiming for certain target market.

Law 3: Establish own brand


Seeing their promotion of other products sales went so well, Jenner sisters rushed to develop their own clothing line, but this brand is quite controversial. Followers who bought complained that regardless of style, the material or cutting are inferior, nevertheless the retailer prices are not cheap.

The economy behind it

Concerns are often raised whether buying products that recommended by internet celebrities is trustworthy or not as products that internet celebrities promoting are not supervised by any regulation as long as they are complied with law. Moreover, they do not have clear responsibilities for consumers who made purchases as a result of their product placement post. Nevertheless, these influencers still make certain impacts on their followers to help either brand build their business or discover their own selling opportunities.

Given the fact that internet star’s every move comes with commercial incentives driven by huge business interests, it is up to followers to identify contexts and contents on Instagram at the moment. Interestingly, followers are willing to invest their time and attention in the absence of interaction with the influencers, as Bateman et. al (2011) discovered that continuance community commitment (i.e. followers have adopted the habit to check on their following influencers’ posts) and affective community commitment (i.e. followers find intangible rewards as browsing pictures are enjoyable) were the form of commitment that have stronger impact on participants’ reply-posting behavior except that normative community commitment in the context of Instagram does not make every participant obligated to post pictures. Therefore the last piece of advise to become Instagram celebrity is to keep followers come back for more and new content of pictures and to sum up, as the internet celebrities mentioned above, they have leaned to what their audience is asking for and show them what they want, and they will become loyal.



Bateman, P. J., Gray, P. H., & Butler, B. S. (2011). The Impact of Community Commitment on Participation in Online Communities. Information Systems Research, 22(4), 841-854.

Robehmed, N. (2016). Kylie Jenner’s Earnings: $18 Million In 2016.Available: Last accessed 8th March 2017.

Lester, T. (2016). T The industry that has erupted within the modeling industry. Available: Last accessed 8th March 2017.

Lankston, C. (2015). ‘Using Kylie in a campaign was risky, but it paid off’: Beauty guru reveals how celebrity fans like Kylie Jenner and Elle Macpherson helped her to build a $100 MILLION brand. Available: Last accessed 8th March 2017.

Morrison, L. (2015). How Do Instagram Stars Make Money? Here’s What Goes On Behind All The Valencia. Available: Last accessed 8th March 2017.

The Insurance Industry Is Taking Advantage of the Sharing Economy

The so-called ‘sharing economy’ has benefited numerous consumers through the value it has added to their lives. Companies such as Uber, Airbnb and Lyft, to name just a few, have taken advantage of the digital technologies humans have developed over the years. However, consumers are not the only benefactors of the sharing economy, the insurance industry has developed products and services specifically catered to its unique characteristics, most notably in the ride-sharing sector, where insurance providers have taken advantage of liability concerns occurring in such ‘sharing’ activities (Traum, Vol. 14:511).

One of the first products developed, the “Metronome”, came from a collaboration between Uber and MetroMile. The device tracks the vehicle of a Transport Network Company (TNC) driver, and is embedded in the Uber application (Traum, Vol. 14:511). It only turns on and activates the required insurance plan when drivers are engaged in TNC services. When the driver is not carrying a passenger, or hasn’t accepted a ride, any liabilities arising from an accident are covered by his own insurance. This product considers both the professional and personal roles of Uber drivers. In a similar fashion, a new plan from Farmers Insurance, on offer since May 2015, supplements a TNC driver’s personal plan with a premium of eight percent (Traum, Vol. 14:511). Many insurances providers have begun to offer similar services to the ride-sharing industry.

Furthermore, the use of such digital technologies has expanded to mainstream customers’ insurance plans. Some companies have developed a chip to be installed on the vehicle during production. Similarly to the Metronome, this device tracks if a vehicle is in use and offers full coverage, to the extent of the customer’s plan, in the case of an incident. However, when the vehicle is parked and the engine is off, the insurance company provides a more limited plan. This enables insurance firms to offer their customer with a more suited, and personalised service.

In the case of Airbnb and other home-sharing services, the lack of legislative development with regards to the coverages of issues common to such activities (Traum, Vol. 14:511). However, insurance providers are aware of the risks that may arise but have yet to adapt and respond to liability issues specific to the home-sharing industry. Together with national governments and sharing economy companies, insurance providers have to strive towards addressing consumer needs; such as protection issues. Furthermore, innovations in this industry can be translated to insurance plans for the mainstream customer, taking the advantage of newly available digital technologies.

Traum, Vol. 14:511. Sharing Risk in the Sharing Economy: Insurance Regulation in the Age of Uber. Cardozo Pub. Law, Policy & Ethics J.

Network Effects in online consumer-to-consumer platforms

This paper focusses on the evolution and growth of online C2C platforms, where other papers mainly focus on the auction system. To examine the evolution and growth, the paper investigates the cross network effects, which means they look at the effect of more sellers on the growth of consumers and the effect of more customers on the growth of sellers. They use data of Taobao, which is the world’s largest online customer-to-customer platform. Taobao is Chinese-based and part of the Alibaba Group. The platform started in 2003 and by December 2012 they had over 7.1 million sellers and 435 million consumers. The transactions made in 2012 totaled 95 bilion dollars.

Taobao started in 2003 with different rules and conditions. After a few months they changed to free pricing and other measures to encourage growth of sellers and buyers. The research uses all the available data that Taobao saved from 2003-2012. This consists of data like what people buy, what product category and what is searched for. The findings imply that the earlier mentioned enhancements accelerate the growth. Moreover, they found that the impact of the seller installed base is much larger on the buyer growth, than the buyer installed base is on the seller growth. Which means that buyers probably inform each other about the amount of sellers and products on a platform, while this happens less with sellers.

If managers know what effects are occurring in their seller and buyer base, they can allocate resources more efficiently. The author discusses three factors that managers can focus at. First, during the introduction stage of the platform, buyers and sellers should be incentivised. For example, through referral bonusses like Uber does. This has a large and long-lasting impact on the growth. Second, the product variety has both a direct and an indirect effect. The direct effect is that new buyers will register. Because of this, more new sellers will sign up to the platform, this is the indirect effect. Third, is the effect of buyer quality. This will attract more sellers, which in turn attracts more buyers. So, the main task for managers is to attract more sellers and buyers with a high quality.

The main strength of the paper is that it uses data from Taobao. The platform does not charge any commissions on the subscription of buyers or sellers, or on the transactions. Instead, it earns money through promotional options for sellers. This means the buyers and sellers can sell and buy for free and this effect is not interfered by any commissions of the platform. Besides this, Alibaba Group gave creditcard payments a more reliable image by launching Alipay, which means there are no barriers for buyers. Moreover, Taobao has a big market share so a lot of data is available.



Junhong, C. & Manchanda, P. (2016) Quantifying Cross and Direct Network Effects in Online consumer-to-Consumer Platforms. Marketing Science, 35(6): 870-893.

The Effectiveness of Branded Mobile Phone Apps

E-commerce is evolving in a tremendous pace. A few years ago, marketing strategies of companies towards e-commerce were based on e-mail or place advertisements online. The last one, online advertisement, is nowadays still a popular marketing-instrument. But what’s changed in the strategy last few years? Almost everyone is having and using it every minute of the day: a smartphone. But, what is so special regarding mobile telephone marketing? It is the effectiveness of branded mobile phone apps.

According to Hutton and Rodnick (2009) an important reason for the popularity of branded apps as a marketing device is their high level of user engagement and the positive impact this presumably has on attitudes toward the sponsoring brand. In contrast to aforementioned ways of marketing, the branded apps are welcomed as “useful,” which suggests that they may be one of the most powerful forms of advertising yet developed. There has been solely research done towards the potential of customized text messages, however hardly research has been done regarding the personal nature of the mobile phone. This study examines how to optimize the promising marketing potential of apps.

An online survey is conducted as pre-test measure. Subsequently, an experiment is conducted, which measures psychophysiological factors,  in order to investigate the effectiveness of branded mobile phone apps. A strength of this study, after the different methods used in this research, is the elimination of self-selection effects. Each participant was asked to interact with all eight test apps during the experiment to eliminate these effects.

This study confirms the positive persuasive impact, increasing interest in the brand and also the brand’s product category through the use of branded mobile phone apps. Branded apps have a large effect on the favourability of brand attitude, but only a small effect on purchase intention. However, there is a difference towards effectiveness among the branded apps. Research emphasized the importance of a creative execution style, which improved the effectiveness. Moreover, applications that used an informational style were more effective at shifting purchase intention, compared to apps that used an experiential style. There is also a difference towards gender. In male participants there is a difference between the psychophysiological measures biometric measure, heart rate, suggestive of the informational style focusing attention internally and thereby encouraging the generation of personal connections with the brand. Within the female participants there is hardly difference.

This study emphasized the increasingly importance of branded mobile phone applications. It is an indication towards the marketing department to focus more and more on mobile phones, and less on physical marketing or e-mail. More specifically, branded apps offer the unique benefits of mobile marketing communications, following consumers wherever they go, and able to be updated with the latest localized information and deals. One thing is for sure, marketing strategies have to focus more on branded mobile phone apps.


Hutton, G. & Rodnick, S. (2009) Smartphone opens up new opportunities for smart marketing. Admap, vol. 44(11), pp. 22-44

The Role of Customer Engagement Behavior in Value Co-Creation: A Service System Perspective

The study
Because engaging customers and developing co-creating customer communities can enhance business performance and customer value there has been a considerable increase in interest in these subjects as of lately. Due to co-creation of firms and consumers the boundary that separates firms from consumers becomes more and more blurry (Grönroos & Voima, 2013). Consumers increasingly participate in content creation, product development, support each other in product use, and promote products, services, or brands to other customers. These actions fall under the concept of customer engagement that aggregates the ways in which customers can influence firms (Doorn et al., 2010). However, academics and practitioners lack understanding on how customer engagement contributes to value co-creation. By using a case study approach on a public transport service system involving consumers, communities, businesses, and governmental organizations, Jaakkola and Alexander (2014) try to improve this understanding. The main strength of this paper is that, Jaakkola and Alexander (2014) are (one of) the first who conceptualize the role of customer engagement behavior (CEB) in value co-creation.

This study shows that CEB affects value co-creation by customers’ diverse resource contributions toward the firm and other stakeholders. More specifically, CEB affects other stakeholders’ perceptions, preferences, expectations, or actions toward the firm. Therefore, CEB affects value processes between the customer and firm, and indirectly value co-creation between the firm and other stakeholders. Resources in this case are not only of informational nature but may also be for example physical labor, skills, and relationships. Besides the aforementioned, the study finds numerous other effects. Firstly, customers’ sense of ownership of the firm’s offering and empowerment in the service system are key drivers of CEB and this is supported by the firm’s provision of access and willingness to cede some control to the community. Secondly, engagement behaviors are motivated by the customers’ need to extend and improve the firms offering, either for personal or collective purposes. Thirdly, other stakeholders may provide engaged customers with recognition, legitimacy, and/or resources which further encourages these behaviors. Fourthly, the drivers, manifestations, and outcomes of CEB are iterative and cyclical, as the positive outcomes for each party further motivate them to engage in or support CEB. Lastly, customer satisfaction, trust, and commitment are drivers and outcomes of CEB, and customers’ motivation to engage relates to their expectation of value outcomes.

Managerial implications
Jaakkola and Alexander (2014) suggest that organizations can improve and differentiate their offering by incorporating the broad range of resources that customers and other stakeholders are willing to invest through codeveloping or augmenting behaviors. This means firms should consider how communities of customers can be involved within the firm and explore the potential to engage diverse stakeholders and their networks of relationships around a common cause, enabling greater customization and augmentation of the firm’s offering. More specifically, when customers feel empowered with passion and establish a sense of ownership of the offering, they are more willing to contribute for the benefit of the firm. Furthermore, through influencing and mobilizing behaviors, engaged customers impact other stakeholders’ willingness to engage with the focal firm and thereby offer a valuable channel to new customer and stakeholder relationships. Lastly, firms can encourage CEB by being open, accessible, and adaptive to customers’ resource contributions, but it requires that firms to some extent cede control over the offering to the engaged customers and other stakeholders.

This sound great, but be critical
Because this study focuses on a public service system, i.e. a railway station that has somewhat of a monopoly status, the generalizability of the findings is somewhat limited. Therefore, the findings may be most applicable to other public sector contexts where resources are limited and common causes can be more easily fostered within communities. However, I feel the findings are robust enough to apply to multiple others communities of stakeholders connected by an interest in a certain offering.


 Jaakkola, E., & Alexander, M. (2014). The role of customer engagement behavior in value co-creation: a service system perspective. Journal of Service Research, 17(3), 247-261.

Grönroos, C., & Voima, P. (2013). Critical service logic: making sense of value creation and co-creation. Journal of the academy of marketing science, 41(2), 133-150.

Van Doorn, J., Lemon, K. N., Mittal, V., Nass, S., Pick, D., Pirner, P., & Verhoef, P. C. (2010). Customer engagement behavior: Theoretical foundations and research directions. Journal of Service Research, 13(3), 253-266.



Online Price Search: Impact of Price Comparison Sites on Offline Price Evaluations

Nowadays, consumers are using the internet as a source of information on products and prices before purchasing a product offline. Price comparison sites (PCS) provide and compare numerous retailers on the most detailed level. These sites can possibly influence price evaluations by consumers in the offline setting. When all this information is available to consumers, it gets extremely important for retailers to ensure consumers buy their products since it is relatively easy to find the better option quickly. Therefore, retailers need to revolve their business models around the consumers, in order to stay ahead of the competition and prevent to lose clients due to the internet.

Literature suggests that consumers may prefer higher priced, well-known retailers which have the impression of being able to fulfill non-contractible benefits such as delivery time (Smith and Brynjolfsson, 2001). Moreover, price comparison sites usually show ratings for retailers to signal quality. Commonly, when there is consensus in user feedback, this can reduce consumer suspicion and thereby increase purchase intentions (Benedicktus et al. 2010). However, it is unclear whether this also applies to the ratings provided by PCS.

This paper investigates how offline price evaluations are affected by price comparison sites by conducting three different studies, of which study 1 will be discussed extensively and study 2 shortly. In the first study, it is investigated if consumers’ price evaluations are affected by reference prices on price comparison sites as well as the retailer ratings. The authors also consider price validity and retailer quality inferences as mediating factors. Price validity means how genuine and obtainable a certain price is in the market. To test these questions, consumers were shown the search results from a price comparison website regarding heart rate monitors. Information included a list of multiple retailers, their prices for the heart rate monitor and the corresponding retailer ratings. Next, participants had to rate the attractiveness of another offer price for the same product and their opinion on price validity and retailer quality. Besides, participants were informed that ratings are composed from customer reviews and that ratings thus reflect customer experiences. The findings suggest that consumer’s subsequent price evaluations are particularly influenced by retailer ratings from price comparison sites. There is a mediation effect from price validity, but that is not the case for retailer quality perceptions. Study 2 finds that consumers are able to gather important information from the PCS search results and can assess distribution characteristics (price level and frequency), which shows that the use of these PCS prices as reference prices is relatively complex.

Figure 1: retailer rating effect on price attractveniss

The study thus finds that consumers use PCS prices as reference prices when they evaluate prices in stores. Retailers that have favorable ratings on PCS serve as a measure in price evaluation for highly rated offline retailers. Offline retailers should consider the prices that occur frequently on PCS searches when setting in-store prices, since these prices highly influence offline price evaluations.


Benedicktus, Ray, Michael Brady, Peter Darke and Clay Voorhees (2010), “Conveying Trustworthiness to Online Consumers: Reactions to Brand, Consensus, Physical Presence, and Suspicio,” Journal of Retailing, 85 (4), 310–23.

Bodur, H. O., Klein, N. M., & Arora, N. (2015). Online price search: impact of price comparison sites on offline price evaluations. Journal of Retailing, 91(1), 125-139.

Smith, Michael and Erik Brynjolfsson (2001), “Consumer Decision-Making at an Internet Shopbot: Brand Still Matters,” Journal of Industrial Economics, 49 (December), 541.






Comparably: a mobile-first solution to bring transparency and equity in the workplace

We are all familiar with the struggles that can come with finding a new job. First, you have to choose a position and company, among the many alternatives out there in the marketplace. Once you made a selection, the long exhaustive selection procedures will take place. At the end, hopefully some of the companies you selected are willing to hire you. However, how do you really know what the best company to work for is? From the outside, a job may look perfect, but many factors, such as work culture and compensation, will only become apparent once you actually start working there. Luckily, Comparably offers the perfect solution to until recently still non-transparent market.

Comparably was founded in March 2016 by Jason Nazar, Yadid Ramot, Mike Sheridan & George Ishii. The founders were aiming at disrupting some of the many technological HR and job search tools by anticipating to the increasing demand in transparency in both culture and compensation within the working environment. Their online platform allows employees to anonymously report their salary, experience level, company location, company size and other aspects. In return, the platform automatically displays where the employee ranks compared to their peers with the same experience level and job position (Comparably, 2016).

Clearly, there are several other major players in the market that offer online HR and job search tools. The biggest competitors of Comparably are LinkedIn and Glassdoor, but Comparably is aiming at cracking the market for business intelligence dominated by Glassdoor and breaking the chain that LinkedIn has wrapped around the job-hunting process for HR professionals (TechCrunch, 2016). While LinkedIn is focusing on ongoing relationships with employees across their careers, Comparably offers a dashboard for (primarily already employed) would-be job seekers looking for a change. And Glassdoor offers analytics for employers, but what gives Comparably a competitive advantage is that the platform offers the ability to sort employees by gender, location, race and time spent at the company. In addition, Comparably beats competition by providing insights on areas where your company could improve (Comparably, 2012).

Business Model Evaluation
The workplace culture review platform serves as social enterprise which survival depends on the added value for both ends of the platform. The two-sided network delivers joint profitability by allowing employees on one side to publicly rate their companies and see how much their peers are getting paid and on the other side, offering companies a variety of HR related tools. For employees and job-seekers, Comparably offers the advantage of having detailed rankings of a company’s culture (including very sensitive topics as discrimination and harassment). For employers, the platform is assisting with recruiting a better workforce and providing opportunities to see how their company culture is ranked and how this can be improved.

Although Comparably only employs 12 people, the platform supports over 1500 companies, including AirBNB, Twitter, Uber, Paypal and Netflix. Each company owns its own corporate profile page and maintains it as a manner to communicate with potential job-seekers. For now, the tool is free to use for employers and Comparably’s business model is dependent on investors. However, the company has plans to change this in the future (Nazar, 2016).

Regarding the institutional environment, the platform is subject to threat of misrepresenting information of companies and fraudulent activity (e.g. automated methods for ranking, phishing). From employees’ perspective, there might be the fear of privacy issues, since the information they provide to the platform is highly sensitive. To ensure correct and true information, the platform requires each participant to sign the Terms of Service (including terms & conditions regarding acceptable use of the platform). In addition, to guarantee privacy, the company adopts a ‘Privacy Policy’ which can be found on the website and application.

Future prospects
Considerably is an innovative company which raised over $12M in financing and is extensively covered in press by e.g. TechCrunch, LA Times and Fortune Magazine. The company was launched in March 2016 with a compensation data tool and 2 months later already added candidate matching, job postings and a company review feature. With their latest addition, their culture analytics dashboard, Comparably captures a huge competitive advantage and has the ability to defeat competition. / blow competition away.

Carson, B. (2016). The 27 best startups that launched this year. From: [Accessed 7 March 2017].

Carson, S. J., Devinney, T. M., Dowling, G. R., & John, G. (1999). Understanding Institutional Designs Within Marketing Value Systems. Journal of Marketing, 115-130.

Comparably (2016). Find Your Ideal Company & Compensation. From: [Accessed: 7 March 2017].

Crunchbase (2017). Comparably. From: [Accessed: 7 March 2017].

Dickey, M.R., (2016). Comparably’s new tool lets companies see how their culture stacks up against the competition’s. From: [Accessed 8 March 2017].

Shieber, J. (2017). Challenging job search and HR giants, Comparably raises $7.25M. From: [Accessed: 8 March 2017].

Tsekouras, D. (2017). ‘Lecture 1: Introduction to Value Co-creation. Customer-centric Digital Commerce, Rotterdam School of Management [Accessed: 7 March 2017].


The added value of online communities

Why do people join online communities and specifically what do they feel it’s the added value of such a community. For example, Facebook, it might give you information about diverse topics or it can make you feel more connected to your friends on a social level. The aim of Mina Seraj in the paper, We create, we connect, we respect, therefore we are: intellectual, social and cultural value in online communities, is to explore the main characteristics of online communities that are able to deliver value for its users.

It’s important to find out what these main characteristics are because then the managers of such online communities can implement these findings to make their communities more interesting and valuable for their users. Furthermore, if you want to create a community from scratch you know what factors are important to make it successful. Figure 1 shows some examples of reasons that consumers want to participate in communities.


Figure 1 CCDC2017 Lecture 6 09/03/2017 Dimitrios Tsekouras RSM Erasmus University


In contrast to other research, this paper focusses on qualitative research methods. They performed a  netnography, which implies that the author actually became a premium member of the forum, which was the subject of the research. is the most active aviation discussion forums focussed on aviation. It has more than 142000 paying members.  Being a participant observer, the author could observe the forum from the inside out and apart from that the content was analyzed and interviews were conducted with active members of the platform. Using a successful platform like to identify the main strengths of an online community is valuable for the research on this topic.

The results showed that the characteristics; intellectual value, social value and cultural value are the main factors that create perceived value. For intellectual value, co-creation of knowledge and the quality of the content are specifically important. The second main characteristic is social value, specifically platform interactivity through social ties on the platform. For example, there are 500 uploads of pictures and hundreds of posts every day on Lastly, the culture value is important. created their own specific culture with norms, values, rules and regulations and this drives participants to contribute and see the value of the platform.

The observations on resulted in the formation of seven roles of contributors that create the added value of the platform. These roles have an impact on the different perceived value characteristics and therefore are important to take into account when looking at your own community.

2017-03-10 (1)

Figure 2 Roles producing online community value

The most important conclusion of the paper is that the different characteristic should exist simultaneously to get the most value of the community. For managers, these finding could help them to create a strong community and understand the community to be able to deliver value to the members and receive monetary value in exchange. (Seraj, 2012)


Seraj, M. (2012). We create, we connect, we respect, therefore we are: intellectual, social, and cultural value in online communities. Journal of Interactive Marketing26(4), 209-222.

CCDC2017 Lecture 6 09/03/2017 Dimitrios Tsekouras RSM Erasmus University


The Central Role of Engagement in Online Communities


(noun) emotional involvement or commitment


You might haven’t noticed but in one way or the other we’ve all interacted on or with an online community. Whether it was while searching for travel routes, computer settings or in a fashion context. Chances are you read some posts until you found what you were looking for and then left the page without contributing. You are not alone in this, 90% of users never or rarely contributes, while 9% contribute 10% of the content and 1% contribute 90% of the content. This is commonly referred to as the 90-9-1 rule. But how can online communities encourage more people to create content and to help recruit others?

This was one of the questions that led Ray and Morris (2014) to conduct their research. More specifically, their goal was to introduce the concept of engagement, which drives pro-social behaviors in the context of open, non-binding online communities. Prior research has extensively recognized the role of engagement in communities, interestingly online community engagement has not been explicitly conceptualized, modeled, measured, or analyzed as a mediating construct in the information systems literature. This paper is the first to do so.

Building on Ma and Agarwal’s (2007) framework the authors propose a model that shows the central role of community engagement and how it relates to different outcomes (Figure 1). Data was collected from 301 users of online communities and structural equation modelling was used to test the proposed model. The developed framework recognizes that online communities are unique socio-technological environments in which engagement succeeds. In particular, members primarily contribute to and re-visit an online community out of a sense of engagement.

Screen Shot 2017-03-10 at 16.04.04

The authors find that members must feel engaged with the online community to actually create content and that members who merely feel satisfied can still help the online community by saying things that might help recruit others. In addition, they found that self-identity verification (the extent to which the way you see yourself matches the way others see you) has an indirect effect on knowledge contribution through engagement. Furthermore,  this paper provide evidence that engagement also mediates the effect between knowledge self-efficacy (the belief that you have the ability and expertise to contribute) and intention to contribute.

The main strength of the paper is its methodology. The authors have applied several models and control variables to ensure valid results. The main managerial implication for community managers is to help members enhance their self-identity, which eventually will lead to more contribution. They can do so by creating signals for members either by letting them choose a badge themselves or by automatically creating signals from prior activities and achievements such as for example”300+ posts on Data Science”.

In conclusion, this Ray and Morris (2014) found evidence that merely satisfaction is not enough to encourage consumers to actively contribute to online communities, but that engagement plays a central role. To get back to the main question raised in the introduction, the key to promoting pro-social behavior (creating content and recruiting others) in online communities is to create the right balance of engagement and satisfaction.



Ray, S., Kim, S. S., & Morris, J. G. (2014). The central role of engagement in online communities. Information Systems Research, 25(3), 528-546.

Ma, M., & Agarwal, R. (2007). Through a glass darkly: Information technology design, identity verification, and knowledge contribution in online communities. Information systems research, 18(1), 42-67.

A central place for all your communities? Reddit is your go to!

A lot of people use online communities for several purposes. The primary reason is to connect to other people, may it be friends, family or people with similar interest. The latter reason has opened doors for the startup of many online communities existing only for a certain interest. These communities are scattered across the internet, dividing individuals across platforms that are close to their interest. However this leaves people, including myself having to jump from one platform to another to reach communities regarding different topics of interest. If I want to be kept up-to-date on technology, but at the same time want to be updated on new game releases and science, it would be easier for me if this information would be all in one place. One platform in particular comes to mind when thinking of a central place for communities: Reddit.

What is Reddit?

Reddit is one of the largest communities in the world with over 200 million unique visitors every month. It was formed in 2005 by Steve Huffman and Alexis Ohanian. It started out with focus on one community: programmers. Soon the platform turned into a place that people could consider a home for discussing anything, no matter how weird or niche it is. With over 7000 active subreddits it shows how the platform is truly used as a place where its users can talk about any topic. Companies often find their way to this platforms in order to engage with their customers, who have created a subreddit for discussion regarding particular brands, products or services or to monitor particular trends that often become apparent first within Reddit . As you can see, Reddit is a versatile platform.


Business Model

The main selling point of Reddit is its subreddits. Subreddits are user-generated topic creations to which other users can subscribe and discussion about this topic can take place. The users (Redditors) create a topic that is then upvoted or downvoted by other users and their opinion of the topic importance. The same system filters out the inappropriate comments from the conversation oriented comments. A few popular subreddits for example are: Science, News, Funny, Gaming, AskReddit etc. Within these subreddits users can create a headline related to the topic, share information, pictures, videos and exchange opinions with other users. Reddit keeps its users engaged by giving them the freedom to decide what they care about and to talk about what is trending for them instead of what the company thinks is relevant. Reddit drives their product by giving up control to the users. The communities appoint their own moderators and rule enforcers and steer their subreddits the way the users want  it collectively (ref). We have come to understand the main operation of Reddit as a community, but how is it monetized? Reddit is earning money in 2 ways:

 Selling advertising space (since 2009)

Reddit has been making money selling advertising space through managed or self-serve ads. Managed ads start at a price of $30,000 and self-serve ads start at a price of $5,00 cost per thousand. These ads are positioned in such a way that it is whitelisted by Google’s AdBlock and earned a non-intrusive status. However ads alone won’t be enough to monetize the platform due to its users potentially looking for alternatives if excessive advertisement takes place, hence why Reddit has not exploited advertisement to the lenghts that they could. Instead Reddit Gold was invented.

Reddit Gold

Reddit Gold is a member subscription plan that gives users premium features when purchased. The features include: removing ads, change Reddit themes, create a custom Reddit avatar, excluse lounge, awards, better comment and community management features and participation in beta-testing (Reddit, 2017). The membership plan costs $3,99 per month or $29,99 a year. In addition to purchasing Reddit Gold it can also be gifted to other users out of goodness or because they have contributed to the community in such a way that a user deems it fit to gift them Reddit Gold. Reddit’s goal is to rely on Reddit Gold for monetization by increasing features and subsequently help support the community as well.

Efficiency Criteria

Reddit creates value by joint creation and participation of user-generated contect. This value creation is not limited to a specific brand, product or service as this platform serves to create value for anything the users wants. As the users can use this platform to facilitate conversation about certain brands, games, technology, politics etc. or even facilitate exchange of products as a marketplace or facilitate a community for finding ideas as part of a company’s challenge, its limitations are far and few in between. Having introduced Reddit Gold, Reddit can profit from the platforms while enforcing ways of improving the platforms with user input, making sure the users and the company iteratively help each other achieve a better massive community which several parties can benefit off in creating more value.




A healthy body and mind is probably the most common answer, when asked what we wish for in our future. Getting seriously ill is of course something we hope to never become, however when faced with this situation getting diagnosed and treated appropriately seems rather logical. But, what if you’ve seen countless medical experts and no one seems to be able to help you? Introducing; CrowdMed.


The creators of CrowdMed understand that, due to an endless amount of different diseases and disorders, it is highly unlikely for any doctor to know every possible condition associated with a specific set of symptoms. To overcome this problem, they use patented crowdsourcing technologies and an online platform that aggregates collective intelligence and facilitates collaboration among medical experts all over the world. The combination of the crowd and advanced analytics helps solve these cases within just days! By using the wisdom of (and collaboration between medical) practitioners and providing personal reports, CrowdMed differs from other platforms such as PatientsLikeMe, HealthTap and iTriage.


So how does it work?

When signing up as a case solver you are officially named a “Medical Detective”. Medical Detectives do not need to be licensed physicians to participate, however CrowdMed does believe in evidence and science-based diagnoses and thus strongly prefers objective medical evidence. In order to actually be eligible for any monetary rewards you need a certain degree of “DetectiveRating”, which is based on a performance and credential-based reputation system. However, you can participate in diagnosing a patient without any form of relevant education. Even I, Nienke with one year of biology experience in high school could help you with your mysterious symptoms.

Patients are asked to fill in an extensive questionnaire when starting a new case. In addition, they need to upload all medical information, all of which can be done anonymously. The patient then decides how long the case will be online and how they want to reward the Medical Detectives, who helped solve the case. This is a based on a combination of points (which increases DetectiveRatings) and monetary compensations.

CrowdMed uses a prediction market algorithm to assign probabilities to each diagnostic suggestion based upon Medical Detectives’ previous performance and behavior. These suggestions are bundled in a report and provided to the patient after the case is closed. The report includes the top diagnostic and solution suggestions, solution details and patient conversations. The patient is advised to these with the doctor.


Joint Profitability?

When uploading a case patients need to pay a monthly subscription of $149 – $749 depending on the specific DetectiveRating degree of the Detectives they would like to work on their case. These amounts seem gigantic. However in the United States, where not everybody is insured, this could be only a fraction of the costs they otherwise would have paid when consulting with doctors on their own. After the case is closed, the biggest chunk is divided amongst participating Detectives and 10% stays with CrowdMed as a commission fee.  Because of the unique nature of CrowdMed (bringing numerous ‘medical’ practitioners together), it is unfeasible for patients to replicate the service without this mediating platform.

Some drawbacks, however…

Firstly, Medical Detectives do not need any medical background to participate and thus the reliability and quality of diagnoses may be questionable. Moreover, by using a prediction market model, diagnoses are based on non-transparent algorithms and thus it is difficult to assess why certain suggestions rank higher than others.

Secondly, when not satisfied with the outcome, patients do not get their money back. In my eyes this is unethical when working with desperate people, as CrowdMed’s only certainty is the fact that they will cash big sums of money regardless of the outcome. Thus, there is no incentive to ensure for high quality services.

Lastly, diagnoses made by the Medical Detectives do not guarantee for correctness nor do they guarantee for any therapy. This all depends on the willingness of the patient’s practitioner. So spending hundreds of dollars on uncertified/self-proclaimed physicians may get you nowhere in the end. However, possible complaints about quality or applicability of the reports are discouraged by an extensive list of legal compliances, member conducts, warranty disclaimers, limitations of liability and a medical service disclaimer. I suddenly feel symptoms of suspiciousness…



CrowdMed (2017, March 9). Frequently Asked Questions. Retrieved from



The Future of Gamified Ad’s: AppOnBoard

For the first time in history mobile gaming has taken a larger share in the global gaming industry than the PC. Mobile gaming is expected to account for more than 34% ($52.5 bn) of the global gaming industry by 2019 (Newzoo, 2016). The market has become highly competitive and extremely saturated with large global players like Zynga, Tencent, EA Mobile etc. In addition to that mobile games are often given for free thus developers need to rely on creative monetization strategies. This thus requires active gamer engagement to recoup the cost of development. With plenty of choice in mobile games and low switching costs, developers are struggling to promote their apps. To eventually find out that users give up during the initial tutorial of the game.


AppOnBoard wants to change that, like the CEO Jonathan Zweig said “we want to take the tutorial out of the app, to the other side of the fence…. Before the app is ever downloaded” (Anthony, 2017). They have patent-pending technology that can create gamified in-game adds with chronological heat maps to track consumer behavior. This allows developers to see how consumers interact with their demo before the game is even completely developed. This aids developers, in turn helping gaming developing companies to weed out potentially bad app ideas.

The chronological heat maps is an integrated monetization boost for advertisers, as they can now sell of their ad space at higher prices because developers gain more analytics. Both sides of the platform benefits from running ad’s on AppOnBoards technology. Their tag lines surrounding their business model is “built by developers for developers”, and as such they state that they will be the next wave of app revenue.

The tool has been built by a team of engineers who have prior experience in building apps for over 200 titles in the App Store. The company has already signed up some of the largest game publishers including Zynga ($765 million Revenue) and Glu Mobile ($223 million Revenue).

Through a unique form of value co-creation made possible through this proprietary technology, developers can now generate better ideas and design through instantaneous feedback, whilst making ad’s more engaging and fun for consumers. Creating a customer centric approach to app game development.

For the complete story watch the following video!

Efficiency Criteria

Their are multiple stakeholders who gain from the new value system created by AppOnBoard. Under the joint profitability formula advertisers gain more money from their advertisement banners, developers gain more analytics and insights from their designs and consumers get more engaging and fun ad’s.

Under institutional arrangements, there are some judiciary implications, AppOnBoard will have to disclose and provide a “up-front explanation of what data is being collected, what they are doing with it, why they are doing and how long they will store it.” They would have to be communicate clearly to all stakeholders involved. This is required under the Consumer Privacy Bill of Rights. This might raise privacy concerns on behalf of consumers who used to have static ads and now are being tracked on their movement and user behavior.

Under social norms in terms of institutional arrangements, it is still yet to be seen how users will interact with these ads’. Users might find them intrusive over time, or they could simply stop interacting with gamified ads at all.

What do you think? Will app developers benefit from using AppOnBoards technology? And how will consumers respond?


New Zoo, 2016. “The Global Games Market 2016 | Per Region & Segment.” Newzoo. N.p., 21 Apr. 2016. Web. 10 Mar. 2017.

Ha, Anthony, 2017. “AppOnboard Offers Fast, Playable Mobile ads.” TechCrunch. TechCrunch, 06 Mar. 2017. Web. 10 Mar. 2017.





Design Your Way to Success: How Sellers on C2C Platforms Can Use Website Design to Stimulate Repeat Buys

Consumer-to-consumer (C2C) online shopping platforms like eBay and Alibaba’s TaoBao are some of the Internet’s most lucrative businesses in terms of both revenues and website visits – and yet they are also a fiercely competitive environment for the sellers who use them, with consumers often only becoming profitable after multiple repeat purchases (Chen, Huang, & Davison, 2016). The biggest threat to sellers’ e-commerce success? Badly-designed websites that send the message that the seller lacks credibility and service quality.

In fact, making a seller’s store or website appealing is essential in C2C contexts, where consumers carefully evaluate each seller due to their perception that shopping on C2C websites is significantly more risky than making a purchase on a traditional B2C platform (Xu, Lin, & Shao, 2010). With website quality being identified time and time again as a cornerstone of e-commerce success (Huang & Benyoucef, 2013), Chen et al. (2016) set out to explore how service, system, and information quality affect buyers’ economic and social satisfaction – and how relational capital (i.e. the relationship that develops between buyers and sellers on C2C platforms) can moderate the influence of satisfaction on repurchase intention.

Based on a survey of TaoBao shoppers, Chen et al. (2016) conclude that information quality (and, to a lesser extent, service quality) influence both economic and social satisfaction – and that, while economic satisfaction is the most important factor influencing repurchases, social satisfaction is only effective at increasing repurchase intention when paired with strong relational capital.

Figure 1. Chen et al’s (2016) model of how website quality affects repurchase intention

Screen Shot 2017-03-10 at 14.42.06

Key practical takeaways

The model that Chen et al. (2016) proposed and (for the most part) validated in their research is quite complex – the implications of their results, however, can be implemented relatively easily by sellers:

  1. Focus on information quality first, service quality second. Up-to-date and relevant content helps buyers navigate the seller’s site with ease and efficiency, and is the most effective way to increase economic satisfaction. Therefore, sellers should prioritise information content elements such as Q&A in order to stimulate repurchases. Service quality – i.e. the timely handling of shipping and delivery, as well as prompt and polite responses to any issues or questions – can increase social satisfaction, and should be the second area of focus for sellers.
  2. Economic satisfaction is a prerequisite for success, and it strongly influences the intention to repurchase. Therefore, sellers should ensure that their price-quality ratio is appealing. However, they should also be aware that price cuts and price promotions are easily copied by other sellers – and therefore should also invest in relational capital as a way to retain customers.
  3. Without relational capital, social satisfaction is not effective at increasing repurchases. Sellers should foster trust and mutual respect with buyers by ensuring that payments are processed fairly, that service and product quality are up to par, and by providing buyers with perks such as personalised greeting cards or small gifts/samples included in the packages. Over time, this can build relational capital and buyer loyalty.



Chen, X., Huang, Q., & Davison, R.M. (2016). Economic and social satisfaction of buyers on consumer-to-consumer platforms: the role of relational capital. International Journal of Electronic Commerce, 21 (2), 219-248.

Xu, B., Lin, Z., & Shao, B. (2010). Factors affecting consumer behaviour in online buy-it-now auctions. Internet Research, 20 (5), 509-526.

Huang, Z., & Benyoucef, M. (2013). From e-commerce to social commerce: a close look at design features. Electronic Commerce Research and Applications, 12 (4).

Learning Never Stops With Top Hat!

These days everyone has smartphones, tablets and computers and they are constantly using them, anywhere, everywhere.. even in a classroom! When you look around a classroom you often see students sitting passively listening and taking notes on their devices and some are even checking social media or watching a funny video of a cat. The question thus arises:

How do professors get the attention of students?

This is where Top Hat comes in! Top Hat is an application that makes it easy for professors to:

  • Engage their students
  • Check readings
  • Take attendance and participation
  • Increase engagement and comprehension.

Top Hat takes those same mobile devices and turns them into engagement tools. Instead of texting friends, students use their mobile devices to interact with the Top Hat application. Top Hats value proposition is that it offers a complete education platform for inside and outside the lecture room for both the students and professors.

So how does it work?

Top Hat’s business model revolves around selling their product directly to professors and students by offering three products including Top Hat Marketplace, Top Hat Lecture and Top Hat Interactive Text which consist of pre-made content that offer a variety of media such as text, videos and interactive elements that help students study.  Through Top Hat Lecture professors can create a community for their students on the Top Hat platform and they can customise their classes making them more interactive and more engaging for their students.Screen Shot 2017-03-10 at 15.20.13.png

Professors can upload their existing slides, create new slides in the platform or find expert course materials by other professors world-wide.  The Top Hat Market provides everything from presentation to question packs to course notes. At the beginning of the class, students enter a special code to confirm their attendance hence saying goodbye to pieces of paper going around the classroom. During the lecture the professor runs Top Hat right
from their tablet allowing them to walk around the class and mark up the slides  while students can view the slides on their devices. Top Hat makes it easy to engage new students in new, creative ways.  The discussion model on Top Hat allows the professor to question students, and in return students can reply either publicly or anonymously and rate their favourite comments. This way it boosts engagement especially for students who normally don’t participate. This is due to the ‘Online Disinhibation effect’, which is the tendency for people to say or do things online that they typically wouldn’t in the in-person world (Suler 321-326). Moreover, Top Hat also allows for on the spot quizzes. While students answer the quiz questions, Top Hat generates a report in real time on the results.  Moreover, Top Hat gradebook shows how the entire class is doing throughout the semester. This provides professors with up to date information on students complete coursework, their test scores and their attendance and therefore cutting administration time for professors.

Co-Value Creation within Top Hat

Top Hat is a win-win situation for both the professors and the students. Professors benefit from Top Hat as it is dependable, cloud based and provide cost savings. Moreover, professors co-create educational value by sharing their class materials and increasing the educational level.   On the other side, students also benefit from the platform as it makes the learning experience more engaging, more exciting, and more interactive. Students can participate in discussions, rate each other work and develop their knowledge by sharing work, opinions and ideas.Students also get more value out of their education and save around 80% vs. traditional books. By replacing traditional books with online content, less books are printed and used hence providing Top Hat a sustainable advantage. Moreover, Top Hat provides around the clock support through including instructional designers to help professors make their lectures engaging and educational.

Top Hat satisfied the feasibility of required reallocation criteria.  and covers several institutional arrangements. The key to success for Top Hat is both parties being actively involved in using the platform. Professors should solely use this form of sharing content with the students while contributing engaging content on the platform. In turn, students will be more actively involved in the platform and as well contribute more.

Say goodbye to the passive traditional learning experience and say hello to exciting, engaging and active classes! 

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“Home – Top Hat”. Top Hat. N.p., 2017. Web. 10 Mar. 2017.

Suler, John. “The Online Disinhibition Effect”. CyberPsychology & Behavior 7.3 (2004): 321-326. Web.