Tag Archive | amazon

F*cked by the Cloud

On the 12th of October, Dell Inc. announced that it acquired network storage giant EMC Corp. for approximately $67 billion, making it the largest tech merger of all time (and the second-largest overall). That same morning, before the merger was actually made official, I came across an interesting article on this topic called: “Dell. EMC. HP. Cisco. These tech giants are the walking dead” (the first episode of the 6th season of AMC’s television show The Walking Dead premiered the same day).

In this article, it is argued that the aforementioned tech giants are, in fact, dead. And here’s why. For decades, these large companies ruled the market of enterprise computing. When one needed to store lots of data, EMC was your main option. It offered the machines and complementing software to the company, in return for a considerable amount of money. However, as EMC was the only distributor of the software, when the amount of storage needed to be expanded, more money was paid to EMC. The same goes for the other companies. In need the need of servers? Dell, HP and IBM were the ones to go to. Networking gear? Bought form Cisco. The provider of database software? Supplied by Oracle.

In the current environment, however, this is all changing. New players have arisen in the market. Players like Amazon, Google and Facebook, who have changed the existing establishment. The biggest change: the Cloud. These internet businesses became so large, that eventually they realized they could not sustain with hardware and software of the established vendors. The sheer quantity made it too expensive and
they were unable to scale on the assets. Therefore, they simply designed their own hardware and software. This made it less expensive and faster. But most importantly, they did not keep the technology to themselves. They have published it to the world, as open source designs, while at the same time offering their own infrastructure to third parties.
This has caused new vendors to emerge, selling the hardware and software solutions the internet giants came up with. Additionally, more and more companies store their data in the cloud – on the infrastructure of the same tech giants.

Then, why don’t the Dells and IBMs of this world do the same and offer cloud storage? They have in fact, but they can’t stretch it too far. Otherwise, they will cannibalize their existing business. Due to this innovator’s dilemma, these companies are – as the author of the previously mentioned article states – “fucked by the cloud”. By using Amazon’s cloud to store data and run software, you simply don’t need the hardware and software from Dell and HP anymore.

So, what should be the right strategy for these companies in trouble? Dell and EMC have chosen to merge, but analysts do not expect this merger to radically reshape the technology market. It might strengthen their position against direct competitors like HP and IBM, but due to the increasing pressure of cloud-storage, it just seems like a bigger fish in an ever shrinking pond.

Bas van Baar (358545sb)





Technology of the week – Amazon Dash and HelloFresh

In our technology of the week project we took a look at two services that target the “modern day’s customer” who demands to get things done fast, with as little trouble as possible, in a convenient and as much as possible fun way.

When watching the commercials (below) of both HelloFresh and Amazon Dash it really stands out much they resonate with what bothers the customer. They build their messages on how they provide solutions to the pains of everyday busy people. Both services aim to make a task that is a regular and time consuming part of everyday life  “easy” or “simple” (Their taglines are extremely similar: “Cooking made easy” and “Shopping made simple”)

HelloFresh, a three year old start-up, which currently operates in seven countries (the Netherlands being one of them) promises to give customer everything that they need for a delicious, healthy, home-made dinner except the chef. They create easy step-by-step receipt, select organic, seasonal ingredients from local providers, and send the exact amounts needed from those ingredients for a meal that can be ready in a maximum of 30 minutes. Apart from the convenience piece HelloFresh also builds on the very common desire of today’s customers to eat healthy and on the environmental friendly packaging and recycling trend. They use word of mouth in an extremely smart way by on one hand providing customers and their friends discounts if they start using the service based on recommendation and on the other hand encouraging the users to share their ready meals on social media. HelloFresh operates in a market where the bargaining power of the buyer is high and of the suppliers low, where – the threat of new entrants is high, given the low barriers to entry, and the lack of switching cost, and last, but not least, where the threat of substitutes is also high so the number of competitors is high and that is one of the reasons why they build a loyal community of customers. After certain amount of meals cooked with HelloFresh users get certificates, can attend breakfasts and dinners where they get to know the providers and share their opinion about the receipts and ingredients.

Amazon Dash is the newest innovation of Amazon, it is a wand with which customers can scan the barcode of anything that runs out in their household or simply just say the missing item “into” the device. These orders are automatically recorded in the user’s AmazonFresh account and once the customer clicks approve it is delivered within 24 hours. In very simple words the Dash ’s promise is that you will never run out of morning coffee or toilet paper ever again. When providing this service Amazon builds on it’s reliable brand, extremely streamline processes and more than 20 years experience in online shopping. On the long run Amazon’s goal with the Dash is to completely eliminate brick and mortar stores and moving shopping entirely online.

Despite being quite different at first look the Amazon Dash and HelloFresh target almost the same customer segment, and both the channels in which they reach their users (delivery and online platforms), their key activities (finding and managing suppliers, storing perishable goods, delivering) key resources (drivers, carriers, packaging, IT systems) and basic cost structure are comparable. Even in their value proposition they both aim to create a convenient experience and save time for their customers, their main difference lies in what exact problem they want to solve for their customer: making it possible to cook home healthy food without the hassles around cooking or never running out of the basic groceries and never forgetting anything during shopping again.

Both have a strong market presence but while HelloFresh has many similar competitors, the Dash has no direct competitor currently. Amazon Dash and HelloFresh work with a business to customer model currently and have the potential to expand to the business to business sector. Although the discussed business models are both innovative, have the potential to decrease or almost eliminate the importance of brick­ and­ mortar stores and change the relation we have to shopping, the Amazon Dash has potential to do even more than that and disrupt whole sectors in the future.

Authors: Group 15
Ekaterina Marinova – 436554
Anargyros Michaletos – 436750
László Nedeczky – 416837
Lina Nota – 440733
Gabriella Pimpão – 437021

Technology of the week – Group 12

B2B eCommerce

Never before have humans been able to interact in such a manner with businesses as is offered online. The sheer magnitude of sales performed on the Internet is demonstrative of the way in which B2C e-commerce has become a cornerstone of modern day commerce. With 1.2 trillion dollars of B2C e-commerce sales in 2013 one can observe the rapid growth and scale of B2C e-commerce, thus, we decided to focus on two of the largest companies for our analysis, namely; Amazon and Facebook.

Amazon Dash

The Dash Button is the latest attempt of Amazon to facilitate the ordering process and make online spending an everyday occurrence. They allow for the replenishment of convenience products under the form of “one-touch” shopping. Some have aptly described the experience of using Dash Buttons as the “end of dashing to the supermarket” (Smith, 2015). The Dash Button was initially unveiled for 18 brands and cost $4.99 per unit, which is refunded once a purchase has been made via the button. The underlying mechanism behind the Dash Buttons relies on Wi-Fi pairing of customers’ Amazon accounts and the Buttons.

Facebook M

Unlike traditional personal assistant, such as Siri, which are fully technology based, Facebook M is partly Artificial Intelligence (AI) and partly human (Hempel, 2015). The concept is that by assisting the AI with a team of so called “M trainers”, which help it with dealing with unknown cases, “M” would be able to perform tasks based on its previous experiences in the long term (Hempel, 2015). Building on case-based reasoning and AI, the application has the potential to perform a wide array of tasks for Facebook users and is truly disruptive to the way consumers could purchase online. The way “M” is integrated into the Messenger interface is through a small Button which would allow users to text Messenger with their requests. Once complete, the user receives notification of fulfillment (Metz, 2015). The simplification of the purchase process is so tremendous that it has the potential to entirely disrupt how B2C e-commerce is conducted.


Amazon Dash and Facebook M both offer a reduction in time the consumer must take when making an order through a device. Yet, they differ in their approach as to how they provide a time-saving feature to customers. Both technologies are incredibly convenient with orders and reservations available from the touch of a button. Although Facebook M runs the risk of not being adopted seen as it might require users to disclose more amounts of personal information than already. Despite their potential to face resistance, one this is certain: they both have the potential to disrupt the e-commerce industry.


Hempel, 2015. Facebook launches M, its bold answer to Siri and Cortana. [Online] Available at: http://www.wired.com/2015/08/facebook-launches-m-new-kindvirtual-assistant/

Metz, C., 2015. Get a peek at someone using Facebook’s new assistan, M. [Online] Available at: http://www.wired.com/2015/09/get-peek-someone-usingfacebooks-new-assistant-m/

Smith, M., 2015. Hack Amazon’s Dash buttons to do things other than buying stuff. [Online] Available at: https://fresh.amazon.com/dash/

Tom Hendry – 366163th

Dennis Huisman – 369919dh

Micaela Arizpe – 368389ma

Theo Fromentin – 371049tf

Dylan Greenfield – 365747dg

Firefly vs. Alipay – Clash of the Giants – Group 18

Hello IS-peers,

A current event that may interrupt the B2C e-Commerce market is Alibaba’s IPO (largest in history) and their move into the western market. Alibaba’s biggest competitor in the western market will be Amazon. Since these giants clash in the near future, it is worth analyzing their technologies which are being utilized to gain or extend their respective competitive advantages.

Amazon – The Firefly technology

Amazon recently published their Fire Phone, which is a real-time online shopping device. In theory consumers are able to scan over 100 million items, get information about these or directly buy them online.

Firefly Advantages

  • Enabling Amazon to bind their customers even more to their online-shopping platform
  • Might be able to to gain a big market share in the mobile commerce sector, which has a rapidly growing demand (Ghose et al., 2013)
  • Due to the additive information customers have about a scanned item, they are less likely to be price sensitive, resulting in higher-priced purchases (Li et al., 2014).
  • Enabling Amazon to gather much more qualitative data about the customer behaviour like tracking shopping routes, favourite places and so on.

Firefly Disadvantages

  • Looking at the current ratings of the Fire Phone it becomes apparent that the Firefly Technology is not flawlessly functioning (Source: http://www.Amazon.com/review/R1XS6V3MAX1BYD/ref=cm_cr_pr_viewpnt#R1XS6V3MAX1BYD). This fact alone already minimizes the potential advantages of the technology.
  • Gathering valuable behavioural data of customers could lead to severe problems with the protective European privacy law.

Alibaba – The technology behind Alipay

The Alibaba Group has several subsidies which penetrate the B2B, C2C and B2C market. All these diversions are accompanied by Alibaba’s Alipay – a payment platform, which provides security to buyer as well as seller.

Alipay Advantages

  • Enables Alibaba sellers and buyers to decrease their business risks since the Alipay system controls the whole transaction process. Thus Alibaba enjoys huge trust of its customers
  • Enables to store much personal and behavioural information, these may be skilfully utilized for advertising purposes.
  • A gate into new product segments. Yu’e Bao is enabling Alipay customers to invest their money saved on the Alipay platform.

Alipay Disadvantages

  • Accumulated data of the Chinese customers may prove to be inapplicable to the European or American market due to cultural differences
  • Alipay will not face the same trust as in China. Customers first have to positively experience the Alipay service such that Alibaba may be able to build a large customer base and collect big data.


We showed that Firefly and Alipay are both information technologies with advantages that have the potential to reinforce their firms’ competitive advantage. However, it was also displayed that each company faces its own business problems. Therefore we propose:

  • Amazon needs to upgrade its Firefly technology which is necessary to actually extract value from their innovative technology.
  • Alibaba needs to recognize the cultural differences between the Asian and western market in order to successfully establish the Alipay system and the whole group in this varying environment.


Ghose, A., Goldfarb, A., & Han, S. P. (2013). How Is the Mobile Internet Different? Search Costs and Local Activities. Information Systems Research, 24(3), 613-631. doi: 10.1287/isre.1120.0453

Li, T., Kauffman, R.J., van Heck, E., Vervest, P., and Dellaert, B. (2014). Consumer Informedness and

Firm Information Strategy. Information Systems Research, 25(2) 345-363

A Google Engineer Explains Why Google+ Sucks: Platforms vs. Products

You probably remember the guest lecture on platform-mediated networks by Prof. Marshall van Alstyne, right? He also shared some slides, and this one on Amazon’s CEO Jeff Bezos caught my attention:

I googled this so-called “Bezos Platform Mandate” to learn more about it. I expected it to be part of an article Bezos published, or maybe a presentation he did.

As it turns out, the quote is part of an infamous rant by Google engineer Steve Yegge, that was accidentally made public. It was meant as an internal memo, highlighting some key differences between Amazon and Google. It provides an honest, uncensored and at times hilarious insight into the differences between these companies in terms of culture.

Read More…

Technology of the week: Amazon vs BestBuy

In this week’s Technology of the Week we have chosen to evaluate and compare the recommendation systems algorithm used by two of the world’s biggest online retailers: Amazon and Best Buy.

Amazon uses a recommendation platform that is unique for each customer. The recommendations are personalized for each user separately so they provide a unique shopping experience depending on the customer’s interests and preferences. The algorithm Amazon uses is called Item-to-Item collaborative filtering. The effectiveness of this algorithm is based on product grouping. Amazon builds a group of neighboring products for each product on its lists. That means that every time a customer purchases or browses a product X, items from the X neighboring group will be recommended. The question that arises is how does the algorithm recognizes which products are connected. In order to define the similar products and to form the product groups referred above, the algorithm finds items that customers tend to purchase together.  Amazon has hundreds of million products listed on its catalogs and over 30 million active customers. That fact makes recommendation a complicated procedure. There are numerous data sources that have to be mined in order to deliver quality recommendations to the users. Useful information can be provided by the shopping cart of each customer, by their wish lists, by dwell time, by the websites that users were before directing to Amazon, by demographical data, by promotional offers through e-mails and so on.  Amazon released in 2010, a feature that could prove crucial for information mining and to improve their algorithm. This is a Facebook application that enables integration of the user’s Facebook and Amazon profile. Amazon retrieves information from the users’ Facebook profiles and their friends profiles and it provides useful product recommendations for the user and gift recommendations when a friend of the social network has birthday. It also recommends products that are popular among friends, depending on the products that have purchased or liked.

Best Buy is one of the biggest electronics retailing companies. In 2009, Best Buy has introduced the semantic web in their online store in an effort to make basic store information easier accessible. Initially, semantic web was used to inform customers about the operation hours, location, and contact information for its physical stores. After the success of the store finder, the idea of the semantic web was applied to the online store. The semantic web is an extension of the web 2.0 where information is positioned in context and is linked to each other by means of formal languages, so it is understood by computers and users alike. With the integration of sematic web to online retailer shops, information can be structured beyond mere product categories. Connections between products are becoming more clear and understandable to both the computer systems and the customers, and changes in product specifications from the manufacturers are automatically updated to the online shops. The semantic web encodes all relevant features for products in RDF triples rather than simple HTML lists. The computer can understand these triples and organize them as required by the customer on a level of detail that goes beyond product categories and includes every detail and specification of the products. The costumer can, then, specify the aspects of the product that he considers essential and get the feedback of the products he was looking for, without having  to browse through product catalogs. Another feature that is possible with the semantic web is to crosslink products between categories for supplementary or related goods. In this regard it is important to notice that Best Buy can also suggest compatible accessories easily. A simple RDF triple stating compatibility on the company site spares the consumer reading and understanding about compatibility.

Each recommendation system has advantages and disadvantages. Amazon provides quality and fast recommendation to its customers by analyzing their preferences and their interests. But there has been speculation about the trustworthiness of the reviews and ratings that are highly connected to the recommendations. Amazon has been rewarding its top reviewers with free products. That’s the reason that has led people to believe that there are indulgent or even fake comments and reviews.

Best Buy enable customers to find the items they are looking for more intuitively and can compare them easily to other relevant products. But the transition from simple HTML to RDF has a high upfront cost, plus the recommendation system overemphasis on product details at the expense of other important activities (for instance product placement, or how to best utilize the data).

Since both firms have success on the online retailing market, we cannot conclude which recommendation system is better. The conclusion that we can make is that Amazon recommendation algorithms is more suitable for experience goods and Best Buy’s system for search goods, due to its effectiveness comparing and finding technical characteristics.

Group A / Team 8