NetworksSocial NetworksCommunication At Work (T. Allen)What Makes It A Network?Sample NetworkAre Your Friends Friends?Network DiagramAre You A “Connector”?Score a point for anyone you know (friends and acquaintances) with that last name. You may count multiple people for the sameR&D Lab Network (T. Allen)Network StructureCorporate ArchitectureStrength of TiesNetwork AnalysisComputer Company CaseOrg Chart Shows Who’s On TopAdvice Network Reveals ExpertsBut When It Comes To Trust…Another Trust ProblemHow the CEO Saw TrustNetworks15.301 Managerial PsychologyJohn S. CarrollCongruence Model(Nadler & Tushman)Environ.ResourcesHistoryOrg’nGroupIndividualInformalOrg’nFormalOrg’nTaskPeopleStrategyFeedbackInputs OutputsTransformation ProcessSocial Networks• Two powerful social principles:– Similarity: people who are similar tend to like each other and spend more time together– Propinquity: people who are in proximity tend to spend more time together• Your friends are most likely people who are similar to you (on what dimensions?) and who are nearby• What about in the workplace?Communication At Work (T. Allen)> 200’ apart, people don’t talk0.350.300.250.200.150.100.05020 40 60 80 100 120 140 160 180 200 220 240- Samples A and B combined- Samples CProbability of communication as a function of thedistance separating pairs of peopleProbability of communicationDistance (feet)Figure by MIT OCW.What Makes It A Network?• Similarity and propinquity tend to be transitive, i.e., A is similar to B, B is similar to C, so A is probably similar to C• Balance Theory – we like things to be consistentABC+++ABC-++ABC-+-Sample Network• Who are your 5 best Name Common Nearfriends at MIT?1_____• What do you have in common with each 2_____(similarity) and how near are they in 3_____space (e.g., same dorm room, same 4_____floor,…)?5_____Are Your Friends Friends?1____ 2____ 3____ 4____ 5____1____XXXX2____ XXX3____ X X X4____ X X5____ XXXNetwork Diagram1____2____5____3____4____JOEJANEJUANJAMALMEJOHNJILLAre You A “Connector”?• “Connectors” (Malcolm Gladwell, The Tipping Point) or “Stars” (Tom Allen) are people who link to many other people• Gladwell has a test (see attached) based on random names from Manhattan phone book• Students average around 20, older people around 40• Connectors score around 100 or moreScore a point for anyone you know (friends and acquaintances) with that last name. You may count multiple people for the same name.Algazi, Alvarez, Alpern, Ametrano, Andrews, Aran, Arnstein, Ashford, Bailey, Ballout, Bamberger, Baptista, Barr, Barrows, Baskerville, Bassiri, Bell, Bokgese, Brandao, Bravo, Booke, Brightman, Billy, Blau, Bohen, Bohn, Borsuk, Brendle, Butler, Calle, Cantwell, Carrell, Chinlund, Cirker, Cohen, Collas, Couch, Callegher, Calcaterra, Cook, Carey, Cassell, Chen, Chung, Clarke, Cohn, Carton, Crowley, Curbelo, Dellamanna, Diaz, Dirar, Duncan, Dagostino, Delakas, Dillon, Donaghey, Daly, Dawson, Edery, Ellis, Elliott, Eastman, Easton, Famous, Fermin, Fialco, Finkelstein, Farber, Falkin, Feinman, Friedman, Gardner, Gelpi, Glascock, Grandfield, Greenbaum, Greenwood, Gruber, Garil, Goff, Gladwell, Greenup, Gannon, Ganshaw, Garcia, Gennis, Gerard, Gericke, Gilbert, Glassman, Glazer, Gomendio, Gonzalez, Greenstein, Guglielmo, Gurman, Haberkorn, Hoskins, Hussein, Hamm, Hardwick, Harrell, Hauptman, Hawkins, Henderson, Hayman, Hibara, Hehmann, Herbst, Hedges, Hogan, Hoffman, Horowitz, Hsu, Huber, Ikiz, Jaroschy, Johann, Jacobs, Jara, Johnson, Kassel, Keegan, Kuroda, Kavanau, Keller, Kevill, Kiew, Kimbrough, Kline, Kossoff, Kotzitzky, Kahn, Kiesler, Korte, Liebowitz, Lin, Liu, Lowrance, Lundh, Laux, Leifer, Leung, Levine, Leiw, Lockwood, Logrono, Lohnes, Lowet, Laber, Leonardi, Marten, McLean, Michaels, Miranda, Moy, Marin, Muir, Murphy, Marodon, Matos, Mendoza, Muraki, Neck, Needham, Noboa, Null, O’Flynn, O’Neill, Orlowski, Perkins, Pieper, Pierre, Pons, Pruska, Paulino, Popper, Potter, Purpura, Palma, Perez, Portocarrero, Punwasi, Rader, Rankin, Ray, Reyes, Richardson, Ritter, Roos, Rose, Rosenfeld, Roth, Rutherford, Rustin, Ramos, Regan, Reisman, Renkert, Roberts, Rowan, Rene, Rosario, Rothbart, Saperstein, Schoenbrod, Schwed, Sears, Statosky, Sutphen, Sheehy, Silverton, Silverman, Silverstein, Sklar, Slotkin, Speros, Stollman, Sadowski, Schles, Shapiro, Sigdel, Snow, Spencer, Steinkol, Stewart, Stires, Stopnik, Stonehill, Tayss, Tilney, Temple, Torfield, Townsend, Trimpin, Turchin, Villa, Vasillov, Voda, Waring, Weber, Weinstein, Wang, Wegimont, Weed, WeishausR&D Lab Network (T. Allen) Typical communication network of a functional department in a large R&D laboratoryFigure by MIT OCW.p.s. look for “stars” and “isolates”6395744495315122032665426504731373472910301159564687375212767241514407439196435411358452367071203637238457716516261651748Network Structure• Density is measured as the number of ties out of the number possible (is more always better?)• Symmetry is whether ties are reciprocated –liking often is, but respect?• Structural holes are places where ties are missing, and therefore opportunities for brokers to gain power or social capital by becoming key links, at the extreme becoming “bowties” where many people are dependent on a single link• Networks also connect externally, e.g., gatekeepers are conduits for external info (in R&D labs, they go to conferences, read journals)Corporate Architecture• If communication patterns follow distance between people, then how is that distance determined?• For face-to-face communication, it’s the architecture of buildings that matters• What kinds of designs inhibit or facilitate communication? E.g., is engineering “inside the fence”?• We are just beginning to understand what new technologies (email, IM, etc.) do to networks. What would you predict?Strength of Ties• Strong ties are like “cohesiveness” in that they create closed systems: “us” and “them”• Granovetter’s famous paper “The Strength of Weak Ties” found that people get jobs through acquaintances, i.e., weak ties, rather than close friends (strong ties)• Hansen found that different kinds of information travels by strong vs. weak ties: you need weak ties to search broadly for quick and simple stuff, but transmission of tacit or complex information requires strong tiesKinds of Networks• We drew a friendship or liking network, but networks can be drawn on other