Did you enjoyed the lecture on B2B e-commerce last week? If you have and you have searched for “Sana Commerce” in Google afterwards, you’ve probably seen both a sponsored (SEA) and an organic (SEO) Sana Commerce link. Did you clicked on the sponsored one? Thanks, you just ate a couple of euros from my monthly marketing budget. Have you clicked the organic link? Really thanks, you just helped me to increase our SEO click through rate (CTR) and hereby my keyword placement and content efforts. As you’ve learned during lecture 4, Google provides companies the option to create sponsored search results in the Google search engine via the Google Adwords application (SEA). These sponsored results will always be placed in the top section of the page, both in the middle and on the right hand side (Li, 2015). Although these sponsored links generate the highest amount of revenue for Google (Li, 2015), they only represent a small percentage of the total search results. The greatest part namely exist out of organic search results, of which the sequence is not based on an auction, but on a companies SEO efforts.
When using the Google search engine, users experience lots of differences between these two different types of search results, for example their placements and the deviating colour of the sponsored search results. But besides of these end user differences, the “back-end” (were all of the search result data is shown, for example the number of clicks and impressions) of these two types of search result differ a lot, mainly in the manner and amount of information they display. Online marketeers, like myself, hereby experience differences in the way and amount of information that is shown. To understand these differences, I will explain how the information presentation in the “back-ends” are differentiated from each other.
For the organic searches, which result from a company’s SEO efforts, Google offers the Webmaster tool, which since recently can be integrated into a companies Google Analytics environment (Support.google.com, 2015). For the sponsored searches, which result from a company’s SEA efforts, Google offers Google Adwords (Support.google.com, 2015). The first difference between these two platforms is their accuracy.The Google Webmaster tool is dominated by rounded numbers. How well did we performed on B2B e-commerce is a question which I get a lot of the time. When I look into Google Webmaster, it will display “50” clicks and “1500” impressions. Although it can naturally happen that numbers are rounded, the existence of only rounded numbers do not create a sense of accuracy. Meanwhile, the Adwords tool is dominated by accurate numbers and always provides a feeling that this information is gathered properly. Secondly, since Sana is a worldwide company, it happens a lot that marketeers from different companies want to compare there SEO efforts, and that I hereby have to filter information on country level. To achieve this in Google Webmaster, seven clicks are required to set up the country filter properly. In Google Adwords? Just 2 clicks. Besides, Webmaster let you filter on Country alone, while Adwords has more than 10 other filters to specify you information further.
What can we learn from this? That Google is protecting its “cash cow” (Li, 2015), their sponsored search results. If Google would provide the same amount of information for both SEO and SEA tools, companies could finetune their SEO efforts in such a way that SEA would be less necessary. The sentence that people are not motivated to perform better when their paid more does not apply to mister Google then..
Support.google.com, (2015). Google AdWords: An overview for advertisers – AdWords Help. [online] Available at: https://support.google.com/adwords/answer/1704410?hl=en [Accessed 5 Oct. 2015].
Li, T. (2015). Session 4: Electronic Markets and Auctions.
It’s the year 2030 and you are walking with your friend to a cafe in a new city. You see this cosy little cafe and both of you decide to enter the cafe. As soon as you enter the cafe the hostess says: “Hello Mr/Ms “YourName”, we have a table near the back of our cafe as seen in your preferences.” When sitting down the hostess asks: “Would you like to order a Cappuccino, like last week, or do you want something else this time?”. You decide to order a Cappuccino and when you sit down you tap on the table to view the menu on the table. You get a list of recommended items in order to your preferences. You decide to order a tuna salad, like always.
This future event with your friend going into a cafe is pure fiction, however the knowledge of the cafe may be not. How is it possible that this café knew that you were in the neighbourhood, and how did it know what your favourite and preferred drinks/food are? The answer: “Smart Dust”
Smart Dust are tiny little microelectromechanical systems (MEMS) that can detect i.e. vibrations, humidity, temperature, light, movement, magnetism, and chemicals. Tiny devices of 2mm each, work as an system to transfer data to each other. Each of those devices has a small “router” in them to send and receive information. The devices have a wireless range of maximum 10 meters. Due to the small range, it is necessary to have a lot of tiny devices close to each other to transfer data on a larger scale. Their energy source is solar energy, because they have a small solar cell and a small battery in them.
The idea descends from Kristofer Pister, a professor at Berkeley. When Pister presented the idea to his colleagues, his concept attracted the US military and Pister received funds to further his work. The first test was in 2001 were six tiny devices (MEMS) were dropped in a field to detect a military vehicle. The test was successful and they even managed to capture the course and speed of the vehicle. Last year a team of Michigan students successfully embedded solar cells in the MEMS to extend their life drastically.
There are many business implementations for Smart Dust. Pister accomplished to gather information about the weather in San Francisco with a radius of 21km using Smart Dust. Defence related implementations are also possible, such as battlefield surveillance and transportation tracking. Transportation tracking is also possible to control inventories. The tiny Smart Dust devices will take over RFID technology in that case. You can also think of product quality control. Some products need to be stored under certain conditions and smart dust makes it easy to monitor temperature, humidity, vibrations etc. There are more business implementation you can think of such as virtual keyboards, smart offices etc.
The main objective for the researches is to extend the life of the devices even more. When companies start to produce Smart Dust the variable cost of one device will be extremely low. The machines to produce MEMS will be costly at the start, but when this technology becomes feasible for companies it will be implemented on a large scale. Researches ask for caution when implementing this technology, because of the environmental impact. No one wants to live in a city with billions of devices floating in the air. Pister did inhale a device (MEMS) and said that it is equal to inhaling a fly. You will cough it up.
Another thing that researchers ask caution for is privacy. Smart Dust devices can measure a lot of things and they are still trying to implement new kind of sensors in the device. It is also possible that Smart Dust will contain microphones to listen in on conversations. Let’s go back to the introduction. It is possible that your clothes, Identity card and maybe yourself will contain Smart Dust which has information about you and will communicate it with businesses. Where camera’s are easy debatable, because they are visible, Smart Dust is not. People cannot see smart dust being there and don’t know if they will be monitored and for what purposes. Another problem is that information gathered by Smart Dust can possibly be stolen by hackers. You can also think of Smart Dust being used to spy on people or businesses. Someone can scatter some device in a house or conference room to obtain classified information.
Smart Dust is a technology with lots of potential and that’s why it entered Gartner’s hype cycle. It will take some more years to make this technology feasible for the market. Meanwhile the discussion how far monitoring of people can go with current technologies will go on and the discussion will intensify if Smart Dust will be implemented.
Kevin Schaap (358985)
M. Kahn, R. H. Katz and K. S. J. Pister (1999) “Mobile Networking for Smart Dust”, ACM/IEEE Intl. Conf. on Mobile Computing and Networking, Seattle, WA, August 17-19, 1999
S. J. Pister, J. M. Kahn and B. E. Boser, (1999) “Smart Dust: Wireless Networks of Millimeter-Scale Sensor Nodes”, Highlight Article in 1999 Electronics Research Laboratory Research Summary.
Hsu, J. M. Kahn, and K. S. J. Pister, (1999) “Wireless Communications for Smart Dust”, Electronics Research Laboratory Technical Memorandum Number M98/2, February, 1998.
Nowadays, we cannot think of a world without social media. For most people in the Netherlands social media is part of their daily activities, it plays a huge part in everyday life. Facebook, LinkedIn and Instagram are the leading social networks in the Netherlands and are very visible and present for most people. But how is Twitter doing? Last year they were not part of the daily conversation and their presence in a positive way in news and magazines was very low.
Twitter has performed very poorly last year and their stock prices has dropped from $36,56 on 1 January 2015 till $24,68 on 1 October 2015. This is an decrease of 32,5% in 9 months which is very large for a company like Twitter which had generated a large brand awareness over the previous years.
How is this dramatic decrease established and which factors influenced this decrease? How can it be that Twitter is far behind on for example Facebook?
Twitter still does not have a permanent CEO to lead the company, since 1 July 2015 Costolo, the former CEO, stepped down. To increase investor confidence, strong, competent, and above all consistent leadership is required. Besides the absence of a CEO Twitter lacks innovations and there is still no strategy for how to go forward. There is almost zero user growth and Twitter experiences a lot of competition from Facebook and Instagram. For example Instagram is distinguishing themselves from competition by offering a wide range of possibilities to modify you own pictures. Twitter must find a way to generate more value for its users, or else the stock price will continue to decrease. If this stock price declines too far, Twitter will become a takeover target. It will become attractive for other social media platforms to take over Twitter in order to increase their customer base or extend their options and features.
In my opinion Twitter is in desperate need of a good CEO, a good CEO is a key factor in creating a sustainable and profitable company. What do you think, are there more options to save Twitter from a takeover?
Prazic, Peter (2015) Here’s why Twitter, Inc.’s stock price is declining http://www.profitconfidential.com/stock/twitter-stock-price-is-declining/ 05-10-2015
NRC.nl (2015) Topman Twitter treedt af. http://www.nrc.nl/nieuws/2015/06/11/topman-twitter-treedt-af/ 05-10-2015
Oreskovic, Alexei (2015) Wall Street is waiting for Twitter’s stock to hit the level where it becomes a takeover target. http://uk.businessinsider.com/twitter-declining-stock-price-could-make-it-takeover-target-2015-8?r=US&IR=T 05-10-2015
On 9 September, Tim Cook (CEO Apple) says: ‘the future of television is Apps‘ (Apple, 2015). Not everyone will agree, but it is almost certain that this industry is on the brink of a huge transformation. The only challenge left for television is the input problem, where people primarily pay for traditional, linear, pay-television services and besides that own a secondary device (e.g. DVD player, Apple TV) for additional content (Yarow, 2015). However, it is unclear if or when the ‘secondary’ service can be a substitute for the conservative primary services. Some predictions state that these new devices (e.g. Apple TV) could turn the television into a dumb piece of glass (Yarow, 2015), since many companies are making a bet that the largest screen in our homes is going to become an operating system like the ones that power our computers and phones (Hempel, 2011).
Many things have changed since devices are connected to the Internet. Millions of independent developers have got the chance to create great applications for multiple devices. The television is next and many start-ups will look for opportunities to offer video experience via applications on products such as the Apple TV (Yarow, 2015). Besides that big companies are forced to adjust their content as well. For example, Jeff Bewkes (CEO of Time Warner) spoke about the company’s plan to move its vast catalogue of movies and TV shows onto the Web (Lyon, 2011). Besides that, products like the Apple TV provide opportunities for all kinds of businesses (e.g. Netflix, HBO) to broadcast their content in a new way on the biggest screen in the house.
To convince the consumer, the only way to win it digital is to keep it simple (Lyon, 2011). Then if the new platform works, the prediction is that the traditional, linear, pay-television services will become secondary, because people will start to wonder why they are wasting money on this conservative service (Yarow, 2015). To make this transformation from traditional television to the Internet happen, some things need to be taken into consideration. Especially content expectancy, social influence, facilitating conditions, hedonic motivation and habit have significant effects on behavioral intention on (mobile) television (Wong et al., 2014). Additionally, Wong et al. (2014) claims that gender and other demographics tend to have a moderating effect on this television behavior. The question remains if online television is better in serving the needs of users than the traditional television service. And will suppliers be able to adapt new technologies to capture value? Research implies that this adaption is needed. For example, the viewer engagement actually is greater when social media is involved (Pynta et al., 2014), and new social possibilities come along with Internet on television.
From the supplier side, the web has the power to make media distribution cheaper and more efficient (Hempel, 2011). On the other hand, the current business model heavily relies on the revenue they earn from licensing. In each country there are able to capture value since it is legally possible to capture value in each geographic region. The web is breaking this business model. Ad rates are much lower on the Internet. Networks cannot collect their fees. Cable companies fear losing our business. Someone has to pay for all that bandwidth we are using to stream our shows (Hempel, 2011). This means that the suppliers must look for new opportunities to generate their revenue. The Internet on television not only brings opportunities, but also big challenges for the current participants, if they want to stay alive.
Vincent Laduc (417658vl)
Apple, 2015. Apple Special Events. [Online] Available at: http://www.apple.com/apple-events/ [Accessed 1 October 2015].
Hempel, J., 2011. What the hell is going on with TV?. [Online] Available at: http://fortune.com/2011/01/03/what-the-hell-is-going-on-with-tv/ [Accessed 1 October 2015].
Lyon, D.W., 2011. JEFF BEWKES AND THE APPLE TRAP. B-School Connection.
Pynta, P. et al., 2014. The power of social television: Can social media build viewer engagement? A new approach to brain imaging of viewer immersion. Journal of Advertising Research, pp.71-80.
Wong, C.H., Tan, G.W.H., Loke, S.P. & Ooi, K.B., 2014. Mobile TV: A new form of entertainment? Industrial Management and Data Systems, 5 August. pp.1050-67.
Yarow, J., 2015. The new Apple TV will blow up the TV industry. [Online] Available at: http://uk.businessinsider.com/the-new-apple-tv-is-going-to-blow-up-the-tv-industry-2015-9?r=US&IR=T [Accessed 1 October 2015].
On 9 September 2015 Apple presented the iPhone 6S, where they claim: ‘The only thing that has changed is everything’ (Apple, 2015). On the other hand, Samsung claims that ’The next big thing is (already) here’ with their new smartphones (Samsung, 2015). Since I need to buy a new phone very soon, I am starting to doubt how different these products actually are.
The acknowledgment must be made that these companies do not make these phones by themselves. For example, Apple has over 200 suppliers to create their products (Apple Inc., 2015). Besides that Samsung aims to strengthen its position as worldwide computer chip manufacturer (ANP, 2015), which implies that they supply other firms to make their electronic devices (e.g. iPhones).
According to Kaufman et al. (2010) these business networks emerge because customers are more informed and therefore increasingly demanding products and services tailored to their specific needs. This results in business networks, which are able to break up their value chain into independent modules (Kauffman et al., 2010) and thereby are able to add more value to the final product (Ketchen Jr. et al., 2004). One of the reasons to participate in a business network is that it accomplishes more as a whole than the value it can capture by its individual parts (Kauffman et al., 2010). Another reason, especially in this technology driven industry, is that business networks tend to be more innovative (Möller & Rajala, 2007) (Gnyawali & Park, 2011). Therefore all these firms help to grow their entire business network (Gnyawali & Park, 2011), to motive more external parties to join the network (Gallaugher, 2014) and further improve their competitive advantage with their final product (Ketchen Jr. et al., 2004).
The uniqueness of Apple’s business network is that a direct competitor (e.g. Samsung) is a supplier for their products (e.g. iPhone). Scientific literature names this phenomenon co-opetion, where end-product competitors are contributing in each other’s value chain. As aforementioned a reason to embrace co-opetion is more innovation (Gnyawali & Park, 2011), but this still does not clarify why for example Samsung might cannibalize its own products. An explanation is that co-opetition is only beneficial when businesses are still able to differentiate with their value adding activities (Ketchen Jr. et al., 2004). Therefore if end-product competition is growing, businesses are trying to further protect their differentiating activities (Ritala & Hurmelinna-Laukkanen, 2009). A good example from Apple and Samsung are the patent wars they are having for the past few years. They are blaming each other for copying each other innovations to protect their differentiating activities. However, co-opetition will still be beneficial for both parties, since another observance states that it results in less vertical integration and more diversification (Gnyawali & Park, 2011). For example, this ensures that Samsung can further grow as a chip manufacturer without the interference of Apple. Additionally, the suppliers of companies such as Apple benefit from the demand they generate (Zhang & Frazier, 2011). Therefore the question about co-opetition should be: do we as a business want to capture value from competitors or establish a greater competitive advantage? (Park et al., 2013)
To be honest I really admire the research done about this phenomenon named co-opetition. However I still can’t figure out my personal issue. Therefore I would like to ask you: what phone should I buy? Since I can’t see the difference between the products of Apple and Samsung anymore after this study.
Vincent Laduc (417658vl)
Anderson, A., Park, J. & Jack, S., 2007. Entrepreneurial social capital: Conceptualizing social capital in new high-tech firms. International Small Business Journal, 25, pp.245-72.
Anon., 2014. In Gallaugher, J. Information Systems: A Manager’s Guide to Harnessing Technology. Saylor.
ANP, 2015. Samsung wil verder groeien als toeleverancier. [Online] Available at: http://www.nu.nl/mobiel/4132940/samsung-wil-verder-groeien-als-toeleverancier.html [Accessed 25 September 2015].
Apple Inc., 2015. Supplier Responsibility. [Online] Available at: https://www.apple.com/supplier-responsibility/our-suppliers/ [Accessed 23 September 2015].
Apple, 2015. iPhone. [Online] Available at: http://www.apple.com/iphone/ [Accessed 1 October 2015].
Gnyawali, D.R. & Park, B.-J.(., 2011. Co-opetition between giants: Collaboration with competitors for technological innovation. Research Policy, 40(1), pp.650-63.
Greve, H.R., Baum, J.A.C., Mitsuhashi, H. & Rowley, T., 2009. Built to Last but Falling Apart: Cohesion, Friciton and Withdrawal from Interfirm Alliances.
Hitt, L.M., 1999. IT and firm boundaries: Evidence from panel data. Information, 10(2), pp.134–49.
Kauffman, R.J., Li, T. & van Heck, E., 2010. Business Network-Based Value Creation in Electronic Commerce. International Journal of Electronic Commerce, 15(1), pp.113–43.
Ketchen Jr., D.J., Snow, C.C. & Hoover, V.L., 2004. Research on Competitive Dynamics: Recent Accomplishments and Future Challenges. Journal of Management, 30(6), pp.779-804.
Möller, K. & Rajala, A., 2007. Rise of strategic nets — New modes of value creation. Industrial Marketing Management, 36(7), pp.895-908.
Park, B.-J.R., Srivastava, M.K. & Gnyawali, D.R., 2013. Walking the tight rope of coopetition: Impact of competition and cooperation intensities and balance on firm innovation performance. Industrial Marketing Management , 43, pp.210-21.
Ritala, P. & Hurmelinna-Laukkanen, P., 2009. What’s in it for me? Creating and appropriating value in innovation-related coopetition. Technovation, 29, pp.819-28.
Samsung, 2015. Homepage. [Online] Available at: http://www.samsung.com/us/ [Accessed 1 October 2015].
Zhang, J. & Frazier, G.V., 2011. Strategic alliance via co-opetition: Supply chain partnership with a competitor. Decision Support Systems , 51, pp.853-63.
That is what you will be seeing more and more on the windows of shops in smaller cities. On September 24th, the I&O research desk presented the numbers of buying (online vs. offline) within the Netherlands. This research showed that non-food shops are disappearing in small cities in the Netherlands (<40.000 inhabitants). This is a huge problem for shops in those cities, which have to close their doors one by one because of the decline of customers. For example, small cities with less than 10.000 inhabitants experienced a 23% drop of shops, which narrowed shops down to almost only food shops and occasionally a Kruidvat or a Blokker. On the other hand, supermarkets keep experiencing a growth: from 6% in large cities to 12% in smaller cities (I&O research, 2015).
The biggest reason for the decline is of course the fact that more and more people are buying on internet. Where 42% of the Dutch had never bought anything online in 2010, this year the number was 17% (I&O research, 2015). This percentage will probably keep on declining.
I&O researched the influence of online shops on the brick-and-mortar shops and concluded that around 40% of the participants explained that their spending in offline shops declined due to buying online and that they buy something online between 1-3 times per month. To measure the influence per sector, a useful indication is the ‘binding percentage’ (Van der Wal, 2015). This percentage shows the part of the spending that is done in a local store. The result showed that especially clothing, shoes and electronics were bought online instead of a physical store.
The food industry does not yet experience the effect of online purchases that much. Food is usually still bought close-by. The binding percentage of food usually is very high, especially in the smaller cities. This is not only due to the fact that it is easy to shop at a near-by supermarket, but for a lot of people in smaller towns, this is also a social encounter.
It is very hard for physical stores to do something about this problem. We have seen many companies falling down because of the shift. Physical stores could think about hiring smaller space (less shelf space offline, and investing online), open only in the weekends (this is a short tail effect, 80% of the revenue is made during the weekend) or participate in an online platform. As platforms are really starting to take over the internet shopping experience, this can really benefit retailers.
Do you think retailers in smaller cities have any chance of surviving? And if yes, what should they do?
I&O Research (2015) Kijken, kijken naar kopen: hoofdrapport [online]. Available at: http://www.ioresearch.nl/Portals/0/Koopstromenonderzoek_Oost-Nederland2015_hoofdrapport.pdf,
Wal, L. van der (2015) Retail vacancy in inner cities: The importance of area and object characteristics [online]. Available at: http://repository.tudelft.nl/view/ir/uuid:b3e5b812-fcf8-446d-9656-a5054e424d0c/
1954 companies where introducing high-speed printers for the first time. These printers where very big and only work for special computers in that time. When time past new printers where available and they became smaller and quicker. Now new technology will disrupt traditional printing methods and we can print almost every item we would like in every material we would like. We can even print items in 3D.
Glow Forge is a new disruptive technology that uses crowdfunding to get the money to start this awesome idea. The idea is not to create a 3D printer but a easy to use CNC laser cutter that could replace or be added to your old traditional ink printer. The following youtube video gives a rough idea of what Glow Forge is and how it works.
Glow Forge is available yet, only as a preorder. There are 3 different types you can preorder now with a 50 % discount. The Glow Forge Basic is the cheapest one and has no ventilation, so this one is not very user friendly. The second one is The Glow Forge Basic with air filter so you can use the printer anywhere there is power and Wi-Fi. The most expensive one is the Glow Forge Pro with filter. This option is special for frequent users, like a makerspace.
Like Glow Forge there are numerous other products that try to disrupt the traditional way of printing. There are lots of potential benefits, but what are the consequence of this disruptive innovation?
- Plastic molding uses 50 to 100 % more energy than injection molding
- Potential health risks from melting plastics
- Extensive use and reliance of plastics. ( we were trying to reduce this reliance)
- Losing money due black market replicating possibilities
- Creating your own guns
- Responsibility of manufactures. ( Who is responsible for a 3D printed helmet in case of accident)
- Bio printing ethics
- Possibility of 3D printing narcotics
- National security risks, 3D printed objects aren’t controlled and tested
- 3D printed objects that come in contact with food
Looking at the above listed possible consequences and thinking of all the possible opportunities 3D printing offers, I have a question. Are these technologies going too fast and can we control and regulate the opportunities and threats ?
You may already be familiar with the concept through MTV’s popular ‘’Catfish: The TV Show’’, an American reality-based docu series about the truths and lies of online dating. If not, let me hereby introduce you to the Catfish: a person who creates false identities to give the impression of being attractive, while he or she actually is a complete or near opposite of that portrayed. Catfishes use various social platforms such as Facebook, Twitter and Instagram in order to particularly pursue deceptive online romances.
The reason of the tv shows’ popularity lays within its power of confrontation and shocking revelations; the filmmakers literary bring together couples who have interacted solely through their LCD screens. What will happen when these romantics meet in real life for the first time after months of years of online dating?
Enough about the show; the purpose of this blog is not to make you watch it or promote it in any sense. However, I do want to address the ‘’dark side’’ of social media on human psychology in here. Catfishing, various addictions, cyber-bullying, and the online child pornography industry are just some examples.
Now let me zoom in on the actual catfishing phenomenon, because I think it may be somewhat entertaining or appealing to you readers. Catfishers now have the opportunity to not only exercise and thereby worsen their mental issues, but also suck others into them. Their mental disorders and lies can now also impact and literary destroy lives of others and I find that very striking. Of course, the victims or #catfished may be too naïve, impulsive or ignorant. But I am wondering if we then need to become suspicious all the time and lose all trust in social media. When will we as a society be able to use social media and internet in a ‘’right’’ way and what would the Internet look like then? What new problems will arise next?
Naturally, our society is also growing on a mental level through the self-help, community, love and connection that this Information Era provides. And of course, people learn from their mistakes, but at what or rather at whose cost?
Luckily, more attention has been directed towards the catfishing phenomenon and people are warning each other. Do you think the upcoming information systems, sharpening safety and security and society’s increasing distrust will allow people to keep stealing others’ information and/or create deceptive identities in the future? Have you ever been #catfished, had any similar experiences or are you an intelligent BIM catfish yourself?
Our technology of the week paper is about MOOCs or Massive open online Courses. These are websites
that provide online education through either apps or websites. Some well known MOOCs are Coursera,
EdX and FutureLearn. In our paper we focused on Duolingo and Khan Academy.
Duolingo is a MOOC that teaches languages. Currently it offers 40 language courses in 32 languages to
over a 100 million users. Duolingo uses gamified learning to teach you words and phrases in the language
of your choosing. The student can work through a lesson-tree and earn experience points and coins by
finishing up these lessons and doing their daily practice.
Duolingo’s business model is where it gets more interesting for a Business Information Management
student. Duolingo makes of use of crowd-sourced translations. How does this work? Duolingo will teach
you the language that you want and gives you practice articles you can translate. These practice articles
are provided by their partners (E.G. Buzzfeed and CNN) who pay to get translated articles. To make sure
all translations are actually correct, Duolingo makes use of the “Wisdom of Crowds” by using an
algorithm to aggregate all translations provided by the students. Furthermore, Duolingo is now
introducing language certificates for $20, currently these are only offered for English proficiency but it
will likely be available in more languages in the future.
To analyse both companies we made use of the SWOT analysis. The strengths of the business model are
that Duolingo’s revenues are not dependent on advertisement and thus visitor numbers do not cause a
lot of volatility in profits. Moreover, Duolingo fulfills needs of language learners but lets them work for
them without the students actually knowing they are doing work. In this way value gets created for the
students who learn a language, companies that get cheap translations and Duolingo who receives money
for providing value to these two parties. Lastly, Duolingo is diversifying its income streams by starting to
sell Language Certificates.
These certificates however, are not recognized by a lot of institutes yet and are therefore of limited
value. We see this as Duolingo’s main weakness in their businessmodel. More on the rest of the SWOT
Secondly, we took a look at Khan Academy which has a completely different way of doing business. Khan
Academy is a non-profit organization that relies mainly on donations to keep their operations running.
Khan Academy offers mostly university level courses in mathematics, economics and STEM. These
courses are also offered in a gamified way. You can earn points to buy upgrades and you can also level
up your avatar like a Pokémon.
Khan Academy’s main strength is that it is highly esteemed among its users and contributors. As
donations is their main source of income it is very important that public relations are well maintained.
Khan Academy has acquired relations that donate regularly, the most noteworthy of their relations is the
Bill & Melinda Gates foundation and Carlos Slim Foundation who of which both owners compete for
being the richest person on earth every year.
However, relying on donations for you existence may not be a sustainable way to function. If one of the
big contributors withdraws from donating regularly, you lose a lot of income that may not be easily
recovered. We identified this as the main weakness of Khan Academy.
Furthermore we identified opportunities and threats that were quite similar for both companies as they
operate in the same industry. Opportunities mainly involved increased internet access in developing
countries. This will broaden the user base of both Duolingo and Khan Academy. This may result in more
revenues for Duolingo and more donations for Khan.
Threats were mostly inherent to information goods. Information goods are easy to copy and therefore
MOOCs in general are easily attacked by substitutes. However, we think that due to network
externalities both Duolingo and Khan Academy are able to mitigate these risks.
In conclusion, we see that even though Duolingo and Khan Academy operate in similar business
environments and offer roughly the same products, they deploy completely different business models
and seem to be very successful in doing so.
Marianne Glas, 437320
Eelke van der Horst, 356523
Minke Huizenga, 333954
Niels Uiterwaal, 437200
Marjolein Volkers, 344064
The debate around the dangers of Artificial Intelligence has been a recurring topic in the media recently. Two main parties emerge: the skeptics – those doubting the AI’s impact on human survival- and the believers – subdivided in two categories: the optimists and the pessimists-.
In this first part I shall treat the pessimistic believers after having laid out some necessary concepts.
First, what is AI? It is the development of computer based systems able to perform tasks usually requiring human intelligence.
Which kinds of AI exist, based on “intelligence” criteria?
We distinguish 3 types of AI. We have Artificial Narrow Intelligence (ANI), also termed as Weak AI, as it only focuses on one restricted domain. For example, IBM’s Watson easily beats the best-cultured Jeopardy champions, but wouldn’t be able to achieve other human related tasks. Presently the world runs only on ANI.
The next big step up on the intelligence ladder, AI would attain Artificial General Intelligence (AGI). At this level, AI is considered as “smart” as human beings in all cognitive abilities.
Eventually Artificial Super Intelligence (ASI) would follow. This AI is countless times more intelligent than humans.
If you want to know more about those terms, I invite you to consult WaitbutWhy’s blog post on AI.
Summarizing one of the key points of that post, we as human should worry about the potential of AI in soon reaching AGI and ASI levels, as technological advances seem to be following an exponential curve. The reason why most people don’t perceive that trend, is that we have a linear vision of technological evolution. But that is a biased perception of reality.
Now that we have the semantics out of the way, let’s get started.
Actually, an increasingly shared belief has surfaced that AI poses a threat.
Not only for our jobs, as koenhut explained in his interesting post, but AI could seriously threaten human kind’s future. The possibility of witnessing ASI and its potential outcomes are subject of intense debate today.
Over the current year, various influential people have voiced their concerns regarding AI, for two main reasons: its potential to self-improve in an increasingly faster fashion combined with the knowledge that technology is improving at an exponential rate.
Those two factors have namely caught the attention of Bill Gates, Elon Musk and Stephen Hawking. They all warn about the potential dangers in trying to develop an as advanced AI as possible. Elon quotes this even as being equivalent to “summoning the demon”.
As a result of this growing anxiety, the institute Future of Life was created in order to raise awareness and to conduct research in making sure AI will not pose a threat to our existence. Future of Life believes that most AI related R&D should not be focused on AI improvement but on predicting and countering all possible negative outcomes related to that technology.
Hereby a passage from the book “The Infernal Device” (Michael Kurland, 1978) illustrating the current concerns:
A group of computer geniuses get together to build the world’s largest, most powerful thinking machine. They program it with the latest heuristic software so it can learn, then feed into it the total sum of mankind’s knowledge from every source-historical, scientific, technical, literary, mythical, religious, occult. Then, at the great unveiling, the group leader feeds the computer its first question:
“Is there a god?”
“There is now,” the computer replies.
The reasons as to how exactly AI can lead to our extinction are too lengthy to describe in one single blog-post.
I however encourage you to discover the blog WaitbutWhy as pointed out by julianderond, to get a good grasp of the potential dangers posed by AI.
You will feel as if you have had a brief look in another dimension, after having read that blog post on AI. And if your curiosity is not satisfied, I recommend you to read the book Superintelligence by the Cambridge philosopher Nick Bostrom, studying existential threats (possibilities of human extinction). For those who do not have the luxury of time, the movie Ex-Machina is a great watch!
In the following post, I will cover some of the grand opportunities AI offers and the other party: the ASI skeptics.
Wikipedia,. ‘Artificial Intelligence’. N.p., 2015. Web. 5 Oct. 2015.
Atariarchives.org,. ‘Of God, Humans And Machines’. N.p., 2015. Web. 5 Oct. 2015.
Futureoflife.org,. ‘The Future Of Life Institute’. N.p., 2015. Web. 5 Oct. 2015.
Pandora’s Brain,. ‘Short Story’. N.p., 2013. Web. 5 Oct. 2015.
BBC News,. ‘Stephen Hawking Warns Artificial Intelligence Could End Mankind – BBC News’. N.p., 2015. Web. 5 Oct. 2015.
BBC News,. ‘Stephen Hawking Warns Artificial Intelligence Could End Mankind – BBC News’. N.p., 2015. Web. 5 Oct. 2015.
In the course Information Strategy we often hear and read the word “Network Effects”. However, in my opinion it is often not obvious what kind of network effects exist, what other similar effects occur, and especially how to differen
tiate “Network Effects” from these other effects. In this block post I will therefore explain two kinds of network effects and will differentiate them from “Economies of Scale”, “Learning Effects” and “Bandwagon Effects”.
Network effects describe the benefit that accrues to the user of a product or service because he or she is one of many who use it (Swann, 2002, p. 417). One of the first and most influential statements on network effects has been those by Katz and Shapiro (1985, p. 424). They define their concept following: There are many products for which the utility that a user derives from consumption of the good increases with the number of other agents consuming the good. In this early paper, Katz & Shapiro (1985, p. 424) have already illustrated that network effects can be divided into direct and indirect effects.
A direct network effect is generated through a direct physical interaction of users. Therefore, the number of purchasers affects the quality of the product. The utility that a consumer of a communication technology derives, depends on the interaction opportunities. For example, the consumer’s utility of a telefax depends on the number of other users that are joining the network. Thus, a user who is joining the network in the early stage can use it only restricted, however, with every new user, the own utility is further increasing. Summarized, direct network effects are caused by interaction opportunities of users and therefore its benefit is higher in bigger networks than in smaller ones (Fleisch, 2001, pp. 86f.).
In contrast to direct effects, indirect network effects are independent from user interactions. Economies of scale cause a utility increase for the provider and can occur due to dissemination of complementary goods. Sterman (2000, p. 12) clarifies this with the following example: The larger the installed base of Microsoft software and Intel machines, the more attractive the “Wintel” architecture became for developers. And furthermore, the more Wintel computers were sold, the stronger the installed base grows and consequently the more compatible software could be sold. In this way, network effects can be expanded from actual network effect goods to compatible groups of goods (Frels, Shervani & Srivastava, 2003, p. 40).
At the same time, limitations have to be presented in order to boarder them from other consumer and producer effects. Wiese (1993, p. 6) named bandwagon effects, economies of scale, and learning effects as economic effects that seem to be closely related to network effects, but are actually caused by other reasons. These effects are grouped depending on if their effects are related to the presence (static) or the past (dynamic) and if they affect the demand or costs.
Bandwagon effects appear on demand side and occur when customer increase their demand since they expect an increased overall demand of this product (Leibenstein, 1950, p.189). When considering network effects, the increasing number of users leads to an increased demand as well. However, in contrast to bandwagon effects this is not affected by imitations, but by the increased value of the network effect good, which is triggered by an increased transaction frequency.
Economies of scale arise when unit costs decrease because fixed cost can be distributed over an increased output. According to Wiese (1993, p. 6) bandwagon effects and economies of scale are static since they occur in the presence and are not caused by past events.
In contrast, learning effects occur when unit costs decrease in dependency of the overall output over time. Kloster (2002, p. 27) states that actual users are gaining experience over time and when a product or services is improved due to past experiences these are called a learning effects. They are beneficial for all future users. Accordingly, the utility increase is a derivative one since the increase appeared due to past dynamic experiences and not by the current number of users or their interaction frequency. Thus, learning effects stay within the network, even if the creator leaves it, whereas network effects are getting lost or rather weakened with network exits (Schräder, 2000, pp. 98ff.).
Base of this block post is my bachelor thesis: Network Effects in Transportation Networks on Basis of Supply Chain Economics. In there I deepened in the theory of network effect. When I heard this term in the lecture again I had the feeling that the concept is not totally clear to everyone. For this reason I decided to sum up the theory of network effects.
Fleisch, E. (2001). Das Netzwerkunternehmen: Strategien und Prozesse zur Steigerung der Wettbewerbsfähigkeit in der “Networked economy”. Berlin: Springer.
Frels, J. K., Shervani, T., & Srivastava, R. K. (2003). The integrated networks model: Explaining resource allocations in network markets. Journal of Marketing, 67(1), 29-45.
Katz, M. L., & Shapiro, C. (1985). Network externalities, competition, and compatibility. The American economic review, 75(3), 424-440.
Kleb, H. (2013). Network Effects in Transportation Networks on Basis of Supply Chain Economics: Application on the Southern Link Transport Hub Strategic Vision in Cranbrook, Western Australia (unpublished bachelor thesis). University of St. Gallen.
Kloster, T. (2002). Gestaltung von Logistiksystemen auf Basis von Netzeffekten. Frankfurt/M (et.al.): Peter Lang.
Leibenstein, H. (1950). Bandwagon, snob, and Veblen effects in the theory of consumers’ demand. The Quarterly Journal of Economics, 64(2), 183-207.
Schräder, A. (2000). Netzeffekte in Transport und Tourismus. Bern et.al.: Haupt.
Sterman, J. (2000). Business dynamics. Boston: Irwin-McGraw-Hill. Available at: http://users.cecs.anu.edu.au/~u3951377/ENGN2225/course-files/wk02-Sterman_Feedback.pdf (visited on 25/08/2013).
Swann, G. M. (2002). The functional form of network effects. Information Economics and Policy, 14(3), 417-429.
Wiese, H. (1993). Lern-und Netzeffekte im asymmetrischen Duopol. Heidelberg: Physica.
Cloud computing is rapidly changing how people use and interact with software. Online cloud-services offer a variety of benefits for both commercial and personal users, such as increased convenience, reliability, decreased hardware costs… In 2006, Google joined the movement with the launch of Google Docs, the company’s first shot at the productivity suites market (Biswas, 2011). Microsoft had been the dominating force in this industry with its renown Office product line. Recently however, Google used the rise of the cloud to enter the market with Google Apps, and managed to capture parts of Microsoft’s market share.
Both companies apply cloud computing to the underlying infrastructure of their productivity suites. Google Apps is a software-as-a-service all-in-one suite that serves four purposes with its products: Communication (Gmail, Hangouts, Agenda, Google+), Storage (Google Drive), Collaboration (Docs, Sheets, Forms, Slides, Sites), and Management (Google Vault, Admin) (Google, 2015). All of these are cloud-based and accessible when an Internet connection is available. Office 365 is a group of productivity software and services with online and offline elements introduced by Microsoft in 2011. It includes access to a group of proprietary software applications that can be installed on almost any device and different operating systems (e.g. Windows, OS X, iOS, Android), as well as cloudbased replicas with cloud storage. These include Word, Excel, PowerPoint and the storage platform OneDrive.
The main differences are characterized by the type of features, functionalities, scope, and most importantly, pricing models. Microsoft focuses on subscription pricing and offering a high-quality, tailored and flexible product line. With ten different plans, ranging from a free subscription to a yearly fee of $264, they offer the most solutions. In contrast, Google focuses on the simplicity of their offer, and on-boarding many customers via their freemium model. There is also the possibility to upgrade your suite with 2 subscription plans: Apps and Apps+.
Predicting who will “win” in the productivity suite industry is difficult and affected by many factors. Microsoft has been the market leader for decades, and Google used the rise of cloud technology to enter the market with a lower-end product, based on ease-of-use and low cost. Thus far, Google has mainly targeted the consumer market and became a competitive player within this market. In the very near future, they will compete head-on with Microsoft for enterprise clients. According to the Head of Google for Work, it is now “ready to scale the business to enterprise clients” (Bort, 2015).
It is however not probable that Google will eliminate Microsoft as a competitor in the long run. Microsoft has an enormous customer base, and has begun offering cloud-services as well as a freemium model. Both firms will need to continuously tailor their products and business models to the changing and diverse consumer needs. Microsoft, seeks to retain their position as the market leader, while Google desires to disrupt the industry by utilizing the rise of the cloud as their differentiator.
Martin Kayser 353884mk
Benedikt Kolbert 353958bk
Kiki Huang 354902kh
Michal Floss 356166mf
Thomas Gratzmuller 357457tg
I recently had the opportunity to visit the Vasa ship museum at Stockholm. The grandeur and the majesties of the ship truly amazed me. The ship itself has a very intriguing story. The story dates back to the 17th century when King Gustavus Adolphus, the King of Sweden, ordered the building of the Vasa. Sweden was at war and the king needed all the ships that he could get at the Baltic Sea.
King Gustav was deeply involved in the design of the Vasa. After the construction of the ship had started, King Gustav noticed that his enemy, the Poles, had somehow created ships with two deck of guns. He immediately ordered for a modification of the design of the Vasa to make it one of the most powerful ships of the time. The ship designers explained to him that with the current construction, the ship would end up with very little ballast in order to support the two decks of guns which would make the ship unsafe to sail. The king, however, insisted on the new design.
In 1628, the ship was done ready for testing. The ship failed its stability test. It started to tilt widely during the test, so much so that they had to cancel the test. Yet, they decided to go ahead with sailing the ship. On August 10th, 1628, the Vasa launched for her maiden voyage. Within 10 minutes of the launch, a stiff breeze knocked the ship sideways and the ship sank.
You must be thinking what this history lesson has got to do with software project management. But the Vasa is a story that is a classic example of a project gone awry and it is very often being relived today in many organizations within the software industry. The following are some of the problems that the Vasa faced:
- Requirements Creep: After the initial design was confirmed and the construction of the ship had started, the design requirements went through many changes. This resulted in an unstable base platform leading to the sinking of the ship.
- Meddling of Senior Management: The King was deeply involved in the design of the ship even though he wasn’t an expert in ship designing. Even though the ship could not handle the modified design, the king insisted on going ahead despite the concerns displayed by the designers.
- Testing Failure: Even after the failure of the acceptance test, the ship was allowed to sail without any rectifications. The test results were covered up in order to meet the strict deadline commanded by the king.
Many software projects in recent times have faced and continue to face these same problems leading to huge failures and losses. Can you think of recent examples of software project failures similar to that of the Vasa?