All posts by 340274re

Will Popcorn Time survive the war?

In one of my previous post I elaborated on the success of user-generated products/ services and concluded that user-generated products outperform designer generated products on almost every performance metric within the first 3 years (Nishikawa et al., 2012).

Popcorn Time is a good example of such success stories. This platform is an illegal video streaming service that gained allots popularity in a really short time. By the end of 2014 it was known that approximately 1.3 million devices in the Netherlands had the software installed and that this amount was rising by around 15000 on a daily basis. It’s a software on which you can search for the film or series that you want and thereafter stream it while it’s downloading. As it appears, the team behind Popcorn Time consists of a set of developers who work partly together on developing the software.
Another success criterion of this application is that they are trying to guarantee the security and privacy issues of the customers. This is also one of the main discussed topics we had during the lectures. They use the so called “Kebrum”, which ensures that their users can stream videos anonymous without being tracked. They claim that they are constantly working on updates to keep their identity and the identity of the users private.
Additional features as chrome cast are also part of the things that Popcorn Time offers. Moreover, almost all the series and movies have optional subtitles.

Popcorn Time places great emphasis on the value co-creation of their system. This last is seen on every description and facts that has to do with the platform. The next picture is just an example of how they describe themselves on the “about” section of the software. popcorn time about They want to make it very clear that they are an open source project.

They are still having massive competition with streaming services like Netflix, but it’s clear that the huge supply from the illegal platform are way above the legal streaming service. The interface is considered as almost identical of the one from Netflix. The next picture shows their interface and how they integrated the ratings from IMDb into their platform. screen tracers

Although this goods point, there are still many risks, for example that the software is taken out  from the net or that the Kebrum leaks all the ip-address from the users. The original Popcorn Time couldn’t handle the amount of risk they were facing and closed the application and then made it an open source in 2014. Since then there are different versions of the application f which the most popular is the Popcorn Time. There is also the Time4Popcorn, Flixtor and Zona: the Russian version. There are people in Germany who received penalties for using the software. The legal (property right) organizations in the Netherlands are not so advanced yet and to our known are not following the users (community). Mostly they are doing research behind the “big boys”, the Popcorn Team.

Now that we have read how good and how bad the Popcorn Time is and what are its potentials. Do you think that this platform will survive the war against the law? Do you think that competition from example Netflix will be able to keep on the track with the Popcorn Time platform?


Nishikawa, H., Schreier, M., & Ogawa, S. (2012). User-generated versus designer-generated products: A performance assessment at Muji, International Journal of Research in Marketing, 30, 160–167.

Too much power?

How many times are you approached by peoples at the train station or at a restaurant with surveys asking on your opinion about the service and the company? Can you imagine that maybe in the future your answers to such surveys may influence the employees’ salary?

It’s so that HTM, the public transport company in The Hague region, has announced last week that they want to adapt their salary system such as that their customers (the travelers) could help on deciding the salary of the HTM employees. Their main idea is to empower the crowd in such an extent that the answers of the yearly “customer-satisfaction” survey (questions based on friendliness of employees, the vehicles, travel speeds etc.) will define the results: the quality of HTM’s customer service. This result will mean that for every 0.1 point increase on the customer satisfaction; will lead to a 0.2% salary increase. As for now the labor unions rejected HTM’s proposition, but they are open for negotiations.

As discussed during the lectures of customer centric and digital commerce, we can relate this kind of ideas to a huge amount of different reasoning. One of them could be the diversity trumps ability expressed on page 258 of (Majchrzak & Malhotra, 2013).  This means that a large diverse crowd of independent strangers may perform better on certain types of challenges than a small number of experts (Majchrzak & Malhotra, 2013). In addition, we can also relate it to the company goals which are for example, the relation to reduction in costs as mentioned by Fuchs & Schreier (2011).

Another nice practical example of where empowering might be going towards, is Incentro. Contrary to HTM who wants to empower their customers to some extent, gave Incentro their employees themselves the power to adapt their own wage.

This type of may be going to the direction of the name-your-own-price as expressed by Hinterhuber & Liozu, (2014). In this case I can name it: “Name-your-own-wage”.

Concluding, in the lecture about Crowdsourcing we discussed several risks and benefits for companies, employees and the customers when empowering the customer/ employees (the crowd). In addition to this last and to relate it to this post, I want to know from you, my readers: Do you think that organizations are giving the crowd too much power? Or do you think the crowd has the right to influence other decision than just the product design, aspects and applications? Would you fill in a survey on a different way when knowing that it may increase or decrease someone’s salary?


Fuchs, C., & Schreier, M. (2011). Customer empowerment in new product development. Journal of Product Innovation Management, 28(1), 17-32.

Hinterhuber, A., & Liozu, S. M. (2014). Is innovation in pricing your next source of competitive advantage? Business Horizons, 57(3), 413-423.

Majchrzak, A., & Malhotra, A. (2013). Towards an information systems perspective and research agenda on crowdsourcing for innovation. Journal of Strategic Information Systems, 22(4), 257-268.

Tsekouras, D. (2015). “Lecture 3:  Ideas & Design”, Consumer-Centric Digital Commerce, Erasmus University Rotterdam, 01-04-2015.

User-generated v/s designer-generated products

(This post is based on the article: User-generated versus designer-generated products: A performance assessment at Muji by Nishikawa, H., Schreier, M., & Ogawa, S.)
In the course Customer Centric Digital Commerce we learn that one of the main reasons for empowering their user communities into the process is to generate new ideas. The authors of this article present a unique data set gathered from the Japanese consumer goods brand Muji, which has drawn on both sources of ideas (user-generated & designer-generated products) in parallel in recent years.

Muji is a Japanese manufacturer and retailer brand of a broad range of consumer goods, with a particular focus on interior and household products. Their products are sold in almost 500 Muji stores in 22 countries. The researchers focused only on the furniture division (20% of Muji’s total sales) and therefore they minimized the potential of confounding effects that arise from comparing different product categories. The observation period was from February 2005 to July 2009 and 43 new products were developed, produced, and introduced to the Japanese market. 37 products were designer-generated, and 6 were user-generated.

Muji invites users to generate ideas for new products. Anyone who registers on their website can participate. Similar to the internal development of designer-generated products, idea generation follows a specific theme (for example limited storage capacity in consumers’ bedrooms due to small room sizes) for which solutions can be proposed.

The Muji firm’s study takes the form of crowd contest, which entail that the participants compete for the price. However, interestingly after the first stage the other users can also comment, vote, and improve on each other’s ideas. This last give the crowdsourcing some degree of the collaboration type.

Their results show an enumeration of performance metrics on which user-generated products were likely superior to internally-generated products:
Total unit sales: 1st year: twice as much as designer-generated products (DGP). 3years: three times more frequently than DGP.
Total sales revenue:1st year: more than three times higher than those of DGP. 3years: Over five times the sales of DGP.
Gross margin:1st year: Four times higher than DGP. 3years: Six times greater, than DGP.
Survival likelihood, Novelty and strategic impact: 1st year: “worst” user-generated product has a strategic impact score close to the average score of designer-generated products. In addition, they outperformed the DGP after 3 years.
Market Performance: Only 17 out of 37 designer-generated products were still on the shelves after three years. In contrast, five out of six user-generated products were still on the market.

Summarizing, this study demonstrate that user-generated products systematically and substantially outperform their designer-generated counterparts in terms of key market performance metrics. However, in their discussion, the authors claim that firms should draw on user ideas in parallel to their established in-house efforts. The overall NPD process entails many more stages, and that decisive in-house efforts and capabilities are needed to convert any promising idea into a successful new product.

In addition, they also conclude that their results show that user-generated products are more complex and takes more times to implement and this last is especially shown in the amount of user generated v/s designer-generated products in the observation period.
The authors claim that one important question that remained unanswered after their study is: What are the specific capabilities that make user-driven firms successful?



Nishikawa, H., Schreier, M., & Ogawa, S. (2012). User-generated versus designer-generated products: A performance assessment at Muji, International Journal of Research in Marketing, 30, 160–167.

Tsekouras, D. (2015). “Lecture 3:  Ideas & Design”, Consumer-Centric Digital Commerce, Erasmus University Rotterdam, 01-04-2015.