Internet Economics כלכלת האינטרנט

1. Internet Economicsכלכלת האינטרנט Class 11 – Externalities, cascades and the Braess’s paradox.

2. Reminder: Course duties • Work in pairs. • Exceptions (single students) are possible. • Presentation and seminar paper. • Same topic • Same partner • Submission of the (optional) problem set – individually - not in pairs. • You are expected to do it by yourselves.

3. Course duties: choosing a topic • Choose a topic: • paper/book-chapter from the list in the course weblog.http://interneteconomicscourse2011.wordpress.com/articles-and-resources/ • Or any other academic paper or part of a book. • See references to the literature in the papers from the list. • In either case, you need my approval for the topic chosen. • Deadline:January 1st, 2011. • I recommend choosing a topic ASAP. • כל הקודם זוכה • This is the deadline for getting an approval. Means that you need to send it before (in case paper is already taken, or not approved for other reasons).

4. Course duties: choosing a topic • Approval methods: • email to me (preferred) - blumrosen@huji.ac.il • Come to my office hours. (email first) • Write a comment in the articles page in the blog. • (shows others that you have already chosen a certain paper)

5. Suggested articles • A variety • Some theoretical/mathematical • Some empirical • Some surveys • Mathematical depth will be appreciated. • Not mandatory, you can also go in depth in other directions. • Papers from related fields may be approved (for example, business, computer science, game theory)

6. סוף מעשה במחשבה תחילה • Please invest effort in choosing the article. • Read parts of it first. • Look at other papers. • Check if the math level is appropriate for you. • Most problems in previous years: students that discovered too late (just before the presentation) that they would like to change a paper.

7. ראשי פרקים • To encourage you to read the paper, you should submit an outline of the presentation by January 12th. • ½ to 1 page. Font 12. Double spaced. • Please send it to the teaching assistant of the course AviLichtig . • avi.lichtig@gmail.com

8. Time constraints • We will schedule the presentations during the semester break. • Please send your hard time constraints (“miluim, ski vacations, (your own) weddings”). • To Avi, by Januray 12th in the same email as the outline of the presentation. • You can also mention soft constraints (“I would like to present before Pesach as I’ll have exams afterwards”), but we may not be able to fulfill them. • After the schedule is prepared, changes are very difficult, very often impossible.

9. Summary: your duties for the next couple of weeks The following actions are mandatory for participating in the course: • Send me (blumrosen@huji.ac.il) an email with the names of students in your team + get my approval for a paper. • By January 1st. • Send Avi (avi.lichtig@gmail.com) an email with: • The outline of your presentation • Your time constraints for presenting in semester B. • By January 12.

10. Today’s Outline • Network effects • Positive externalities: Diffusion and cascades • Negative externalities: Selfish routing.

11. Decisions in a network • When making decisions: • We often do not care about the whole population • Mainly care about friends and colleagues. • E.g., technological gadgets, political views, clothes, choosing a job,. Etc.

12. What affects our decisions? • Possible reasons: • Informational effects: Choices of others might indirectly point to something they know.“if my computer-geek friend buys a Mac, it is probably better than other computers” • Network effects (direct benefit): My actual value from my decisions changes with the number of other persons that choose it.“if most of my friends use ICQ, I would be better off using it too” Today’s topic

13. Main questions • How new behaviors spread from person to person in a social network. • Opinions, technology, etc. • Why a new innovation fails although it has relative advantages over existing alternatives? • What about the opposite case, where I tend to choose the opposite choice than my friends?

14. Network effects • My value from a product xis vi(nx): depends on the number nxof people that are using it. • Positive externalities: • New technologies: Fax, email, messenger, which social network to join, Skype. • vi(nx) increasing with nx. • Negative externalities: • Traffic: I am worse off when more people use the same road as I. • Internet service provider: less Internet bandwidth when more people use it. • vi(nx) decreasing with nx.

15. Network effects We will first consider a model with positive externalities.

16. Network effects • Examples:VHS vs. Beta (80’s) Internet Explorer vs. Netscape (90’s) Blue ray vs. HD DVD (00’s)

17. Diffusion of new technology • What can go wrong? • Homophily is a burden:people interact with people like themselves, and technologies tend to come from outside. • We will formalize this assertion. • You will adapt a new technology only when a sufficient proportion of your friends (“neighbours” in the network) already adapted the technology.

18. A diffusion model • People have to possible choices: A or B • Facebook or mySpace, PC or Mac, right-wing or left-wing • If two people are friends, they have an incentive to make the same choices. • Their payoff is actually higher… • Consider the following case: • If both choose A, they gain a. • If both choose B, they gain b. • If choose different options, gain 0.

19. A diffusion model (cont.) • So some of my friends choose A, some choose B. What should I do to maximize my payoff? • Notations: • A fraction p of my friends choose A • A fraction (1-p) choose B. • If I have dneighbours, then: • pd choose A • (1-p)d choose B. • With more than 2 agents: My payoff increases by a with every friend of mine that choose A. Increases by b for friends that choose B. Example: If I have 20 friends, and p=0.2: pd=4 choose A (1-p)d=16 choose B Payoff from A: 4a Payoff from B: 16b

20. A diffusion model (cont.)

21. A diffusion model (cont.) • Therefore: • Choosing A gain me pda • Choosing B will gain me (1-p)db • A would be a better choice then B if:pda > (1-p)db that is, (rearranging the terms) p > b/(a+b) • Meaning: If at least a b/(a+b) fraction of my friends choose A, I will also choose A. • Does it make sense? When a is large, I will adopt the new technology even when just a few of my friends are using it.

22. A diffusion model (cont.) • This starts a dynamic model: • At each period, each agent make a choice given the choices of his friends. • After everyone update their choices, everyone update the choices again, • And again, • And again, • … • What is an equilibrium? • Obvious equilibria:everyone chooses A.everyone chooses B. • Possible:equilibria where only part of the population chooses A. “complete cascade”

23. A B Diffusion B B B B A B B B B A B • Question:Suppose that everyone is initially choosing B • Then, a set of “early adopters” choose A • Everyone behaves according to the model from previous slides. • When the dynamic choice process will create a complete cascade? • If not, what caused the spread of A to stop? • Answer will depend, of course, on: • Network structures • The parameters a,b • Choice of early adopters B B B

24. Example • Let a=3b=2 • We saw that player will choose A if at leastb/(a+b) fraction of his neighbours adopt A. • Here, threshold is 2/(3+2)=40%

25. Example 1

26. Example 1 Two early adopters of the technology A

27. Example 1

28. Example 1 A full cascade!

29. Example 2 Let’s look at a different, larger network

30. Example 2 Again, two early adopters

31. Example 2

32. Example 2

33. Example 2 Dynamic process stops: a partial cascade

34. Partial diffusion • Partial diffusion happens in real life? • Different dominant political views between adjacent communities. • Different social-networking sites are dominated by different age groups and lifestyles. • Certain industries heavily use Apple Macintosh computers despite the general prevalence of Windows.

35. Partial diffusion: can be fixed? • If A is a firm developing technology A, what can it do to dominate the market? • If possible, raise the quality of the technology Aa bit. • For example, if a=4 instead of a=3, then all nodes will eventually switch to A. (threshold will be lower)  Making the innovation slightly better, can have huge implications. • Otherwise, carefully choose a small number of key users and convince them to switch to A. • This have a cost of course, for example, giving products for free or invest in heavy marketing. (“viral marketing”) • How to choose the key nodes? • (Example in the next slide.)

36. Example 2 For example: Convincing nodes 13 to move to technology A will restart the diffusion process.

37. Cascades and Clusters • Why did the cascade stop? • Intuition:the spread of a new technology can stop when facing a “densely-connected” community in the network.

38. Cascades and Clusters • What is a “densely-connected” community?If you belong to one, many of your friends also belong. • Definition: a cluster of density p is a set of nodes such that each node has at least a p-fraction of her friends in the cluster. A 2/3 cluster h

39. Cascades and Clusters • What is a “densely-connected” community?If you belong to one, many of your friends also belong. • Definition: a cluster of density p is a set of nodes such that each node has at least a p-fraction of her friends in the cluster. h A 2/3 cluster

40. Cascades and Clusters • What is a “densely-connected” community?If you belong to one, many of your friends also belong. • Definition: a cluster of density p is a set of nodes such that each node has at least a p-fraction of her friends in the cluster. • Note: not every two nodes in a cluster have much in common • For example: • The whole network is always a p-cluster for every p. • Union of any p-clusters is a p-cluster.

41. Cascades and Clusters In this network, two 2/3-clusters that the new technology didn’t break into. Coincidence?

42. Cascades and Clusters • It turns out the clusters are the main obstacles for cascades. • Theorem:Consider: a set of initial adopters of A, all other nodes have a threshold q (to adopt A).Then: 1. if the other nodes contain a cluster with greater density than 1-q, then there will be no complete cascade. 2. Moreover, if the initial adopters did not cause a cascade, the other nodes must contain a cluster with a density greater than 1-q. Previously we saw a threshold q=b/(a+b)

43. Cascades and Clusters In our example, q=0.4 cannot break into p-clusters where p>0.6 Indeed: two clusters with p=2/3 remain with B.

44. Cascades and Clusters • It turns out the clusters are the main obstacles for cascades. • Theorem:Consider: a set of initial adopters of A, all other nodes have a threshold q (to adopt A).Then: 1. if the other nodes contain a cluster with greater density than 1-q, then there will be no complete cascade. 2. Moreover, if the initial adopters did not cause a cascade, the other nodes must contain a cluster with a density greater than 1-q. Previously we saw a threshold q=b/(a+b) Let’s prove this part.

45. Cascades and Clusters • Assume that we have a cluster with density of more than 1-q • Assume that there is a node v in this cluster that was the first to adopt A • We will see that this cannot happen: • Assume thatv adopted A at time t. • Therefore, at time t-1 at least q of his friends chose A • Cannot happen, as more than 1-q of his friends are in the cluster • (v was the first one to adopt A)

46. Cascades and Clusters • It turns out the clusters are the main obstacles for cascades. • Theorem:Consider: a set of initial adopters of A, all other nodes have a threshold q (to adopt A).Then: 1. if the other nodes contain a cluster with greater density than 1-q, then there will be no complete cascade. 2. Moreover, if the initial adopters did not cause a cascade, the other nodes must contain a cluster with a density greater than 1-q. Previously we saw a threshold q=b/(a+b) Let’s prove this part.

47. Cascades and Clusters • We now prove: not only that clusters are obstacles to cascades, they are the only obstacle! • With a partial cascade: there is a cluster in the remaining network with density more than 1-q. • Let S be the nodes that use B at the end of the process. • A node w in S does not switch to A, therefore less than q of his friends choose A • The fraction of his friends that use B is more than 1-q • The fraction of w’sneighbours in S is more that 1-q • S is a cluster with density > 1-q.

48. Today’s Outline • Network effects • Positive externalities: Diffusion and cascades  Negative externalities: Selfish routing.

49. Negative externalities • Let’s talk now about setting with negative externalities: I am worse off when more users make the same choices as I. • Motivation: routing information-packets over the internet. • In the internet, each message is divided to small packets which are delivered via possibly-different routes. • In this class, however, we can think about transportation networks.

50. Example • Many cars try to minimize driving time. • All know the traffic congestion (גלגלצ, PDA’s)