Diffusion Of Innovation

In chapter 19, we were introduced to the diffusion of innovation theory. This theory, explains the process of accepting new ideologies and technologies. In other words, this theory examines how “new behaviors, practices, and opinions spread from person to person through social networks, influencing the adoption of new ideas.” The article, Senior Tech helps baby boomers come of digital age, elaborates on new inventions that satisfy baby boomers current health needs. As today’s boomer population approaches retirement, the market for technologies that monitor health is expected to grow.

When it comes to technological shifts, millennials are know to be early adopters while baby boomers are more likely to be laggards. These generational gaps are often fueled by attitudes towards technological changes. To marketers, when promoting their product this becomes an obstacle. In this scenario, the diffusion of innovation theory helps to understand the underlying theories on these generational gaps. As we learned, individuals in a network are usually influenced by their neighbors’ decisions which spreads across the network’s links.Networks based on direct-benefit effects have the following characteristics: you have certain social network neighbors and the benefits of adopting a new behavior increase as more of your neighbors adopt it. An example, the article gives that showcases direct-benefit effects is the adoption the RealPad made by AARP and Intel, which aims to make it easier to initiate video calls with families and friends. This adoption not only helps users but also strengthens the community.

http://www.usatoday.com/story/tech/2015/01/30/senior-tech-gadgets/21820299/

 

Pay-Per-Click

In Chapter 15, we are introduced to the concept of pay-per-click. Pay-per-click is an advertising model used by advertisers to direct traffic on ads. In this model, advertisers pay a publisher for each ad clicked. The goal for using this model is to increase awareness for an advertisement. Because of this advertisers are willing to pay high prices for pay-per-click ads. For instance, in the book Networks, Crowds, and Markets, it states that for subjects like “loan consolidation” and “mortgage refinancing” the pay-per-click rate can often reach $50 or more.

The article, How different demographics ‘really feel about ads, elaborates on the proper uses of this model. According to eZanga, a digital marketing firm specialized in pay-per-click states that 75% of these ads are clicked unintentionally. To solve this problem Michelle Brammer, director of marketing at eZanga.com advises marketers to be more aware of user experience. According to Brammer, due to the evolution of ad formats it is extremely important for companies to know their audience and give them what they want to see. Demographics can help narrow down possible ways to attract these markets.

Secondly, Brammer recommends advertisers to carefully review the placement of their ads. In class, we learned that the auction procedure is used to determine the price for ad placement. In a basic set-up for a search engine auction, there are a certain number of advertising slots to be sold to a population of potential advertisers. Each slot holds a click through rate, which higher slots generally get higher click through rate.

http://www.marketingdive.com/news/how-different-demographics-really-feel-about-ads/416148/

Landing The Job You Want Through Your Network

In today’s day and age social media accounts have become so useful that companies are now asking their hiring staff to use them to look for potential employees. That is why keeping your social media account professional is very important. It can hurt you if you have negative stuff on there as well. The author in the article goes on to talk about how knowing someone is still how companies would rather hire people. As was discussed within class, networks are very important and the more people you know the better. Network effects play a key role in the hiring process.

Social media has made it very easy to stay connected and build your network. People definitely should take advantage and try to use social media to their benefit and build a greater network of people and stay in touch with them over time. Many times this is how people land their jobs; by the people that they know.

Companies hire people through their social networks because someone has vouched for that person, and it gets rid of the uncertainty of how that person will behave. Companies would more rather hire someone that a present employee already knows, rather than an unconnected person outside of their social network.

One of the disadvantages of relying mostly on networks when hiring makes diversity in the workplace diminish. I think companies should not always hire people from their social network to keep the network of people more diversified.

http://www.strategy-business.com/article/Social-Network-Effects-in-Hiring?gko=33101

Earth Day: Using game theory and AI to beat the poachers

This article discusses briefly problems that arise when wildlife preservers and forestry are being poached by poachers. It can be difficult for park rangers because often the scale of the reserve is usually large for the rangers to cover. this problem affecting the effectiveness of the ranger causes game theory to come into play. the game according to researchers is called “green security games” “they are being created to use mathematical and computer models of conflict and cooperation between rational decision makers”. “By this, predictions of the behavior of adversaries can be generated, giving rangers better clues as to where to patrol”. the purpose is to increase the slim chance that rangers will catch poachers. two companies PAWS (Protection Assistant for Wildlife Security) and SORT (Simultaneous Optimization of Resource Teams) aimed at protecting wildlife and forestry respectively, have been the main benefits of this data analysis process using game theory read article for more.

Earth Day: Using game theory and AI to beat the poachers

 

Adopting to Facebook’s new “Like” Alternative

Facebook has just recently launched a new update towards their trademark of the “like” button on Facebook. Like many other updates in which Facebook creates and changes on their platform. People are constantly forced to adopt to these new changes based on the aspect that even if one doesn’t like the change. People will eventually accept and adopt on the new change even if they do no like the specifics of the change. With the change in the “Like” trademark on the Facebook platform. As more people are starting to learn of this new change, more people are starting to adopt to this and will utilize this new function. Similar to how nodes will adopt based on a cascade behavior in a network. As soon as more people start using a function, people will become curious and start to learn to adapt to this new exciting feature to the “Like” function. Although this is a new feature added, Facebook can utilize this function to figure out the behavior of people who would adopt or just stay with using the traditional like button. Clusters will form for those who adopt and those who do not adopt.

Source:

http://www.forbes.com/sites/kathleenchaykowski/2016/02/24/facebook-no-longer-just-has-a-like-button-thanks-to-global-launch-of-emoji-reactions/#4b0b9e794994

 

GSA Launches Reverse Auction Platform for Use by Government Agencies

A reverse auction is a type of auction in which the roles of buyer and seller are reversed. In an ordinary auction also known as a forward auction, buyers compete to obtain a good or service by offering increasingly higher prices. In a reverse auction, the sellers compete to obtain business from the buyer and prices will typically decrease as the sellers underbid each other. A reverse auction is similar to a unique bid auction as the basic principle remains the same; however, a unique bid auction follows the traditional auction format more closely as each bid is kept confidential and one clear winner is defined after the auction finishes. This article from 2013 discusses the benefits that a reverse auction procedure will bring to government procurement processes. GSA believes that such procedures will have saved as much as 17 percent through use of reverse auctions.  “With GSA offering front loaded discounted pricing as a starting point through its BPAs, the reverse auction approach will provide additional savings to the government”.

http://www.gsa.gov/portal/content/174799

Power-Law Distribution & Stock Markets

Basing their investigation on the hypothesis that trades made within large populations cause major fluctuations in the stock market investigators found, with the use of power laws, that they were able to closely analyze the fluctuations in stock prices, number of trades, and the size of the trades that occur. Interestingly, they found that the exponents  used to represent various types of markets were similar for all of those varying markets, even for those markets that are in other countries. Two of the many equations used in there investigation were to be applied to the US stock. However, they decided to use equations (2) and (3) for the Paris Bourse, the French stock exchange, and lead it them to some interesting conclusions.

Initially they applied these equations to the evaluation of 35 million transactions within the 30 biggest stocks in the Paris Bourse between the years 1994 and 1999. They learned that the power laws that were specifically for the US stock market also held for a foreign market. It also showed that equations (2) and (3) could be Universal.

Additionally, they showed that the power laws used in the financial data came about when the trading was conducted in an optimal manner. They also demonstrated the relationship between fluctuations in prices and the number of trades performed.

The graph above demonstrates the collective distributions of the returns from 1,000 of the largest countries between the period 1994-1995. You can see that this bared a slight resemblance to the graph for the power-law distribution of Web-page links, as it is linear and downward sloping.

Gabaix, Xavier, et al. “A theory of power-law distributions in financial market fluctuations.” Nature 423.6937 (2003): 267+. General OneFile. Web. 21 Apr. 2016.

Link to Source

How to Make Good Guesses

An article written by Tim Harford describes the use of Bayes’ rule in order to make good and accurate guesses. Bayes’ rule describes the probability of an event, based on conditions that might be related to the event. There is an exact equation for Bayes’ rule and it is as follows:

P (A|B) = P (B|A) * P (A) / P (B)

Harford explains that when considering an event in which a guess or assumption can be drawn from it, you should take and combine any related information you have about the event. Considering all of this information, you will be more likely to make an accurate guess about the event that is occurring. He explains that psychologists have asserted that people do not make good guesses because they ignore some piece of obvious information altogether. Harford proposes the the information that gets ignored, usually a quantitative number, is the base rate and the effects of neglecting the base rate has been known since the 1950s.

He gives an example that asks him to guess what will happen the UK economy in 2016. Using his reasoning, one would suppose that there is a 10 percent change the UK economy will begin a recession this year. The logic behind this is in the fact that there have been seven recessions in the past 70 years. In this case, the base rate or ignored information is the 10 percent. Harford goes on to explain other ways this reasoning process can be applied. In particular, he talks about its usefulness in the field of screening programs such as DNA tests for potential criminals.

He concludes that it is extremely easy to jump to conclusions about probability. He emphasizes that it is important to take a step back and consider all of the information before you go and make a guess about something. He proposes that you should get in the habit of finding the base rate of any event and use the Bayesian way of thinking whenever you are trying to make a good guess.

ft.com/…/7d01cd92-da87-11e5-98fd-06d75973fe09

 

 

Decline in Apple Watch Sales, explained by network effects

In this article, the author adopts network effects to explain the causes of decline in sales of Apple Watches.

“In an article by Jay Yarow, he adds a figure from the web that shows interest in the Apple Watch has dropped below that of the iPod. Furthermore, he states that’ People, like myself, have sold their watches. Other folks are find that life without the watch isn’t so bad.”- Cornell University, Networks, Course blog for INFO 2040/CS 2850/Econ 2040/SOC 2090

R(x) refers to the intrinsic interest of a consumer with an x reservation price while f(z) refers to the benefit of each consumer from having z fraction of the population using Apple Watch. R(x)f(z) refers to the function that shows consumers who are fond of the benefits offered from purchasing and using apple watches when the users’ population is at large. Therefore, essentially, the decline of apple watches purchases could be explained by people’s realization of apple watch’s useful purposes. Maybe people just don’t find apple watches that worthy to have money spent on, that’s why users’ population declines which causes low intrinsic interest on the product from the public.

https://blogs.cornell.edu/info2040/2015/11/20/network-effects-in-the-market-of-apple-watches/

Pagerank toolbar

We learnt about the essence of PageRank when it comes to wed-surfing. It is a system developed by Larry page and Sergey Brin and its basic idea is that: if a page is important, it will be cited by other important pages. This is the feature that google has within its google toolbar PageRank, it essentially determines what would show up in searching results.

In the second article, it mentions about how Google is planning on removing Toolbar PageRank. This means that individuals using tool or a browser that shows PageRank data from Google, will soon lose their privileges of doing so. Google’s decision, however, doesn’t take away page rank data internally within the ranking algorithm; which means that when people are searching for information on Google, they could still visit sites with high clicking rate, giving them high chance of locating their desirable information. It is just that the external PageRank values are being taken away.

 

Source :

https://websiteadvantage.com.au/Google-Toolbar-PageRank#heading-ToolResult

http://searchengineland.com/google-has-confirmed-they-are-removing-toolbar-pagerank-244230