Summary ‘Technology of the Week’: Digital Transformation Business Models Sharing Economy (Airbnb) vs. Long-Tail (Netflix)
We evaluated and compared two different business models of two successful companies. Both have used technological transformation to reach success. We looked at Airbnb, which is using the sharing economy model, and Netflix, which is using the long-tail business model.
The sharing economy concept means the optimization of resources through the redistribution, sharing and reuse of excess capacity in goods and services. The rise of mobile internet and social media has reduced the threshold to borrow resources from others enormously. Benefits for sharing economy include: saving costs, reduce negative environmental impact, stronger communities, etc. (https://en.wikipedia.org/wiki/Sharing_economy).
The long-tail concept means selling small amounts of a relatively large number of unique or less well-known products. It is very common in the industry of online internet retail.
Airbnb is an example of the sharing economy concept: it is a digital platform which allows local renters to rent out their free rooms to worldwide travelers. The business model is built on sharing of resources in the community. In earlier years, travelers booked their night stays at hotels, hostels, etc. Now, it’s also possible to stay at local houses through the platform of Airbnb, for mostly cheaper prices. IT plays an important role, in creating and maintaining platforms that are supporting the idea of the sharing economy (http://www.triplepundit.com/series/rise-of-the-sharing-economy).
Netflix is an example of the long-tail concept. It is the world’s largest company in online movies and series streaming (https://help.netflix.com/help). They offer a monthly subscription that allows unlimited access to movies, series and documentaries. Members can search for any movie; also less popular content is available as this is a characteristic of the long-tail. In the years before Netflix, they were just physical video libraries, where someone could rent a video for a limited period of time. Netflix made the transformation by offering online movie rentals. Internet is the critical factor to implement the long-tail business model, which most of the time resulted from digital transformation (http://bizshifts-trends.com/2015/02/04/chasing-tail-business-anatomy-long-tail-business-model-taste-obscurity-overwhelm-choice/)
In our paper we have used the business model canvas in order to show the business models of Airbnb and Netflix in a very simple way. The canvas model is easily understandable and shows every key aspect of a business. We have also used Porter’s Five Forces to show the competition within the industry of the chosen companies. In our paper we try to make future predictions based on the results of the Five forces analyze.
When we compare the business models, we see these similarities:
- Very few physical assets.
- Range is quite large, internationally oriented.
- Cost leadership plays big role.
- Very dependent of the internet.
- Customers around the sharing economy model are more price conscious
- The sharing economy is more dependent of their customers (suppliers at same time). Long- more dependent of suppliers (companies).
For the future, we expect the markets around these business models to grow. Because of people getting more price conscious, and getting more aware of the fact they can compare everything at the internet, the sharing economy will be more popular in time. The long-tail model is already getting popular, with all current possibilities of buying from the internet. A threat for Netflix will be that due the fact that downloading movies for free is so easy, people doesn’t want to pay anymore. Maybe more focusing on placing advertisements in films, and possible upgraded accounts to avoid the advertisements?
Vera Crijns – 374956
Pervin Demirtekin – 370681
Özlem Karakuş – 357166
Harm-Jan Rijneveld – 370370
Oscar Chong – 384993
Since the late nineties Augmented Reality (AR) was tested and developed for specific purposed (i.e. military use). Various companies already launched their AR/VR device. But what is AR in fact? AR combines real world objects with virtual computer-generated objects. Together, they form a supplemented real world environment (Azuma, 2013).
We focused on two different applications of AR in the form of the app Blippar and the Microsoft HoloLens. Below is briefly explained how AR is applied in these two products. Blippar makes use of Mobile Augmented Reality (MAR). MAR uses the same principles as AR: it provides an experience to the customer that combines both real world as artificial aspects (Höllerer & Feiner, 2004). Hence, it does not create a complete artificial world, but rather uses the real world in real-time as its user interface (UI) whilst integrating layers of information. The Microsoft HoloLens is a device to enter the AR world. The HoloLens is in the form of goggle-like glasses.While with MAR users experience AR from a device in a selected area of their environment, with a wearable AR (WAR) device users experience AR in their entire surroundings.
A comparison of the two models resulted in several similarities between the two models, but also significant differences. While Blippar is potentially disrupting the well-established advertising industry with is AR app, Microsoft is competing with other tech giants to conquer the newly developing wearables market using its HoloLens. However, both models are heavily dependent on network effects. The more people are using Blippar, the higher the incentive for businesses is to advertise using their AR app. The HoloLens, on the other hand, is dependent on the input of app-developers on their platform and the customer base in order to attract app developersa. The more people are using the HoloLens, the more likely it is that new apps are developed for the device. In turn, this attracts additional customers.
If the Hololens can overcome future threats such as privacy issues and substitutes, and the usage of wearables will be adopted by the mass market, it might capitalize on the advantages the device can offer. However, before the mass market will adopt the HoloLens, it will probably be used by business first for more specific tasks. Blippar, on the other hand, is expected to move its app to the wearables market as well. Instead of focussing solely on the advertisement market, it wants to become the “first true AR search engine” (Blippar, 2015). Although they have invested in WaveOptics, an augmented reality display pioneer, the option remains that they will be acquired by one of the established tech giants. However, for their mobile application, internal weaknesses and external threats inherent to smartphone use must be overcome first. Foremost, increasing data-use and the battery drain of smartphones halt widespread use.
Do you think the HoloLens is able to avoid the faith of the Google-Glass and that Blippar can be the new AR Google?
Azuma, R., Baillot, Y., Behringer, R., Feiner, S., Julier, S., MacIntyre, B., “Recent Advances in Augmented Reality”, IEEE Computer Graphics and Applications, vol.21, no. 6, pp. 34-47, November/December 2001, doi:10.1109/38.963459
Höllerer, T., & Feiner, S. (2004, Januari). Mobile Augmented Reality. Retrieved September 10, 2015, from http://www.cs.ucsb.edu/~holl/pubs/hollerer-2004-tandf.pdf
Blippar. (2015, 9 9). blippar.com. Retrieved 9 10, 2015, from blippar: https://blippar.com/en/about
SID’s: 358545sb, 356175jh, 345222lh, 363966lk, 341304lr
For marketers it is useful to know this information, as they are able to attribute the value of their campaigns across different devices/channels. In order to know this information, you need to have access to certain data of course, and this is where privacy concerns come in.
There are different methods when it comes to cross device tracking. One of them is the deterministic approach. It relies on personally identifiable information. This is where users have to sign in into a platform like Google and Facebook, who have huge user bases. As long as the user stays logged in, they can track you and target you on multiple devices.
The other one, a less simpler method, is the probabilistic tracking method, which collects information like operating system, browser cookies, webpage visit and mobile device IDs to create a digital fingerprint which is then linked to a user’s device. Through algorithms and (statistical) analyses, they are able to create a (most likely) match between devices, which roughly said can lead to concluding that this smartphone and this tablet most likely belong to the same person.
The probabilistic method is invisible to consumers and they cannot control it, like they could with cookies. The marketing industry defends itself by saying it does not hold any personal data as they do not know any names or email addresses. All they have are those device profiles. It is not being used to identify an individual.
Personally, regardless of what information you collect from someone, an email address or a device type, I think it should still be viewed as personal data. A smartphone can also be considered as quite something personal nowadays. The Federal Trade Commission says cross device tracking is a sign of a post-cookie world and is even holding a workshop this November to explore the privacy issues and security risks.
First of all, I do understand the FTC and others, are concerned about privacy and they try to ensure that consumer’s privacy maintains protected. Privacy is a hot topic, it always will be. I also understand that there are people who are simply opposed to entities tracking them. But regardless of understanding their point of view, I personally don’t really see a (privacy) problem. Or maybe it is because I used to be an online marketer myself and I understand the value of this type of collected information and the insights it can provide marketers.
Besides that, we as consumers also benefit from cross device tracking, because things get more convenient, e.g. shopping on your smartphone first but then being able to finish the purchase on your computer at home. And for that, you have to give up some privacy. We live in a world where (online) privacy nowadays is hard to fully maintain. A possible solution is opting-out, or perhaps informing consumers the same way they are informed about cookie placements. But how will the transparency regarding data collection work out in the end? Any thoughts on this matter or the solution for it? Or perhaps you would like to share how you feel about these privacy concerns? 🙂
Linda Tram – 355313kt
Artificial Intelligence (A.I.) is the intelligence exhibited by machines or software. As technology becomes more sophisticated at a very fast pace, A.I. is becoming seriously realistic development rather than just a sci-fi geek’s wet dream. The idea of self-thinking and/or self-aware machines is nothing new and the speculations about whether A.I. is a positive development or not vary greatly. A dystopian scenario of A.I. going wrong was portayed in The Terminator and The Matrix movie series. A more subtle example is the movie Ex-Machina that was released on only recently (Watch this one!). The discussion about A.I. is however no longer in the hands of movie writers and directors.
Artificial intelligence is the attempt to recreate human thoughts, creating a machine with intellectual abilities. The first question to spring to mind is: why do we need machines to do more than assembly line and repetitive processing work? The answer lies with computers themselves. Although the possibilities of what computers can calculate are limitless, they will always be constrained by the input. The computer is incapable of solving problems autonomously . In other words, it can only solve problems it has been programmed to solve, rather than being able to analytically solve problems by itself.
Many industries are interested in having these kinds of capabilities. Examples are the automotive (self-driving cars) and aviation industries, transportation, and gaming and hospitals and medicine sectors. I would like to get into the detail of a much more controversial environment; the weapons industry. Companies have been heavily investing in autonomous weaponry. On the one hand these companies argue that A.I. will make battlefields/warzones ‘safer’ for civilians. On the other, big names in the technology-scene (e.g. Steve Wozniak, Stephen Hawking) are asking governments to stop these developments to prevent an A.I. arms race. In the wrong hands, A.I. weaponry is highly dangerous. Tesla CEO Elon Musk even went as far as calling it more dangerous than nukes. Well-known scientist Stephen Hawking supports him with this notion as I quote
“Humans, who are limited by slow biological evolution, couldn’t compete and would be superseded”. In other words, machines that can update themselves will evolve at a much pace than the human race. He even calls it the potential end of the human race.
Personally I would not go as far as Mr Hawking and I do see a lot of benefits for specific industries. I can’t however ignore that serious negative aspects A.I. can bring with its development. Machines at this point are only able to mimic human behavior rather than initiating it themselves. It will be some years, maybe decades, before the major breakthroughs will become to appear of true A.I. I just hope by that time humans have figures out how to stay in control.
What are your thoughts on A.I and how/where it should be applied? And do we need some sort of a control mechanism over scientists to prevent the dark side of A.I.? Or is it all just sci-fi based fear of the unknown?
By Max van Hilten
Internet Exchanges for used books: An empirical analysis of product cannibalization and welfare impact.
In this blog post I will provide a summary and discussion of the article Internet Exchanges for used books: An empirical analysis of product cannibalization and welfare impact, written by A. Ghose, M.D. Smith and R. Telang. This article was published in Information systems research in march 2006 and can be accessed for free. The URL to the article can be found in the reference list.
The market for used books is nothing new. Even before the rise of the internet people have been buying, selling and sharing used books. Since the inception of the online market platform amazon.com this process has become much easier. In contrast to a brick-and-mortar bookseller, Amazon is not limited by geographical location or shelf space, and can sell for a lower price.
Groups like Association for American publishers believe that used-book sales through Amazon will cannibalize new book sales and even “threaten the future of authorship.” (Russo, 2014). Ghose, Smith and Lang put it to themselves to quantify and publish the effect of used book sales though amazon on the welfare for all stakeholders, and it is these findings we will analyse.
Let us start with the theoretical analysis.
The authors identify two ways the market for used books has an effect on the market for new books. These effects are dubbed the price effect and the substitution effect. The price effect works as follows: when there is a market for used goods, such as books, a consumer will be willing to pay more for the product because he can sell it later on the used-goods market. A consumer that values a book at $25 will be willing to pay a maximum of $40 when he knows that he can sell this book on the secondary market for 15. This mark-up, which is equal to the second-hand price is a direct welfare gain to the original seller.
The second-hand market also creates a substitution effect: For many consumers, new and used products are substitutes. Some people who would otherwise have bought a new product will instead buy a used version. This is the cannibalization the authors guild is afraid of.
The welfare gain or loss to the publisher is therefore the net effect of the price effect minus the substitution effect. A positive number means welfare gain, while a negative number means welfare loss.
The empirical evidence seems to indicate that the substitution effect outweighs the price effect. The authors’ results show that publishers lose about $45 million, or 0,03% in gross profit per year from amazons used book market. Consumer surplus is estimated to be around $67 million annually, and Amazon’s increase in gross profit from used books amounts to about $88 million annually. The net effect on welfare is therefore positive, with consumers of books and amazon’s shareholders being the clear winners from this development, and traditional book publishers losing out.
According to the researchers’ data, only 16% of used book sales through amazon cannibalize new book sales, while 84% of used books would not be sold without amazon. This 84% helps explain the net welfare gain. Amazon sells these books above cost, therefore creating producer surplus. Consumers value the books above their sales price, which is where the consumer surplus comes from.
What about the authors? Are they helped or hindered by the rise of amazon?
The researchers did not investigate the effect amazon has on the authors themselves, which could be an interesting topic for further research.
One effect on author welfare that must be considered is what is known as the “Long tail effect.”
Because physical stores have limited shelf space, they generally only sell items that are popular. This is great for authors of popular fiction, but that means there is less space in the store for niche books. This is unfortunate for the authors of these books, but do the customers ever care? According to the Long tail theory, the answer is yes. The theory of the long tail effect postulates that the demand for goods that are not sold in physical stores might as big as, or bigger than, demand for goods that are. Because amazon.com and similar online platforms are not limited by shelf space of physical location, they are better equipped to fill this demand. This is great news for authors and consumers of niche books, and an additional source of welfare gain.
Source: Brynjolfsson, Yu and Smith (2006)
There is also an additional threat to the welfare of authors that was not mentioned in the articles: the rise of e-books. Traditionally, the net profits of a book were split evenly between publisher and author. For e-books , the author receives a much smaller share of net profits. The division of profits differs from publisher to publisher however, and this topic is still hotly debated between authors, publishers and amazon. Only time will tell how the market for e-books will develop.
Since the inception of amazon.com the market of used books has grown to a size never seen before. While it is natural for publishers to worry that this will cannibalize new book sales, this fear is largely unfounded. New and used books are imperfect substitutes at best, and many book sales would not have occurred without amazon. Because the platform is less limited by physical constraints, amazon can serve niche markets in a way physical stores cannot, thereby increasing welfare for consumers and writers of niche books.
Will e-books help or harm authors? How will the market for books, new and used, develop from here? Can traditional booksellers capitalize on the digital revolution? I’m interested to read your thoughts and ideas in the comments.
Ghose, A., Smith M.D. and Telang, R. (2006), Internet Exchanges for Used Books: An Empirical Analysis of Product Cannibalization and Welfare Impact, Information Systems Research Vol. 17, No. 1, March 2006, pp. 3–19
Brynjolfsson, E., Yu, H. and Smith M.D. (2006), From Niches to Riches: Anatomy of the long tail. Sloan Management Review, 2006, Vol. 47, No. 4, pp. 67-71.
The Authors Guild (2014), Letter from Richard Russo on the Amazon-Hachette Dispute
How do you stay up-to-date on what is going on in Tech world?
Living in a society in which nothing goes unseen, one should be selective on what he or she chooses to see, otherwise you might be overwhelmed by all kinds of impressions which might not at all be relevant to your interests. Traditionally, a lot of knowledge came in through the local newspaper, a type of media which limits the control you have on learning what you want to learn. Nowadays, the News is a rapidly developing industry. News can be followed through traditional channels such as the television or the mentioned newspaper, but recently, multiple new channels have been added to the possibilities.
A good example of this is the Dutch company Blendle, which allows you to only buy specific articles of papers and magazines which you are interested in. Another is the phone application Appy Geek which allows you to only receive news about very specific topics within information technology. The web blog we are using now is a good example as well. To this, numerous other websites, applications and social media pages can be added, which can provide you with the news you are interested in.
However, how do you get to part of the internet which perfectly matches to your desires? I would say helping each other out would be a great way to start. I am sure most BIM students would like to be aware of what is going on in the world of technology. Some of us might be very familiar with the ins and outs of Information Technology and Strategy, some might not…
Therefore, my request to all of you is, to SHARE with us the media you are following to keep up-to-date on News which might be interesting for the whole group of BIM students. Facebook pages, LinkedIn groups, News applications or websites, Youtube Channels, Journals, Television programs and anything else you can possibly think of. Also, a motivation on why and how your suggestion is interesting for all of us is of course always welcome. I am very much looking forward to your comments!
Author: Colin van Lieshout