All posts by cvdessenburg

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.

Do traditional findings on social ties and WOM hold for eWOM?

Different from Word-of-mouth, online word-of-mouth is on a one-to-world platform. It has access to the unlimited reach of the Internet to share opinions and experiences. Another difference is that the electronic nature of eWOM makes the reader unable to judge the credibility of the writer, anonymous posts exist, which means profit-motivated messages can be posted. This paper focusses on the influence social effects have on the value that consumers place on information gathered in their search. It is interesting to know what are the differences between the influence of social ties on WOM and eWOM, because in this way it is possible to understand the value of the source in eWOM environments.

They investigate the data from a website where you can rate your professors, In previous research, academics believe that this website is rather used for entertainment than as a source of information to choose a professor. In this research they argue that the website is used for its intentional purpose, as statistics show that 6 million ratings have been posted, which means there is evidence that students invest time in rating the professors.

482 US college students participated in a survey related to RMP usage, course selection, professor selection and demographic information. The survey resulted in another reason to believe the website is used as a source of information. 96 percent of the students was aware of and 94% of them used the website to select a professor. The main reason why the students use is to reduce risk. For example, the risk of a decrease in GPA and a less interesting class, because of the way of teaching. They also found that just 36% of the students had ever rated a professor themselves and most part of them did not rate more than 2 professors. Most part of the users is passive and reads the content generated by other users. This is a low number, but in line with studies of online behavior.  The results show that the website is more important in the decision making than talking with friends and an academic advisor.

In contrary with WOM, in eWOM situations users find anonymous online forum sources more important than strong friendship ties or weak tie sources. On the other side, the theory for homophily holds, people utilize more information from homophilic sources than from heterophilic sources. Which means that people use more frequently the information from people with the same gender, age and interests. This applies for both WOM and eWOM according to this research.

For websites in the same area or with the same purpose the findings above are important to know how to provide the best and most useful information to its users. By this, they can understand that suggestions based on strong friendships are not useful in eWOM situations, but that people with the same interests are more likely to use eachothers information.




Erin M. Steffes, Lawrence E. Burgee, (2009) “Social ties and online word of mouth”, Internet Research, Vol. 19 Iss: 1, pp.42 – 59. 

Plan who you’ll cross paths with on Tripr

People like to travel together with family and friends. Tripr is a new way of experiencing this. It is an app in which you enter where you are travelling to and when is your trip. Besides this, it has a function like Tinder, you can put preferences for who you would like to meet during your trip. Tripr will then show users who will be in the same city during your given dates and who match your criteria. Because you are able to enter all these details before, you will be able to meet new travel mates months before your trip.

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