CISummit 2013: Ron Burt, The Social Origins of Your Reputation: The Social Psychology of Competitive Advtantage
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CISummit 2013: Ron Burt, The Social Origins of Your Reputation: The Social Psychology of Competitive Advtantage

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CISummit 2013: Ron Burt, The Social Origins of Your Reputation: The Social Psychology of Competitive Advtantage CISummit 2013: Ron Burt, The Social Origins of Your Reputation: The Social Psychology of Competitive Advtantage Presentation Transcript

  • Social Origins of Your Reputation the social psychology of competitive advantage Related teaching and research materials can be downloaded from my website (esp. course handouts “12brokerage, ”34closure,” and a book chapter “Network Structure of Advantage”): http://www.chicagobooth.edu/faculty/directory/b/ronald-s-burt.
  • Trust and Reputation Can Be Critical: To the extent that a broker is advocating something new, there is no guarantee that the proposal will work in our market, with our company processes, staffed by our people. The proposal involves uncertainty, so it requires trust; the more uncertain the proposal, the more trust required. A. High Status is a Good Signal B. Regardless of a Banker’s Status Are you trusted by the people youPositive Reputation Is Sufficent are trying to bridge? of Positive Reputation, but Low These are data averaged across a few hundred investment bankers in the mid-1990s sorted by reputation into those with positive (solid dots), average (grey dots), or poor (hollow dots are bankers in the bottom third of peer evaluations). Graph is from Figure 2.8 in Burt, "Network Structure of Advantage" (2013 manuscript). The boutique investment bank, Moelis — "Best Global Independent Investment Bank" in 2010 and "Most Innovative Boutique of the Year" in 2011 — nicely illustrates the competitive advantage of reputation as an entrée to brokerage opportunities (free Moelis case at www.sbs.oxford.edu/reputation/cases). Network Status (eigenvector score / mean score) to Get High Returns to Brokerage Z-Score Compensation (total annual) Strategic Leadership Creating Value, Contingencies: The Social Capital of Brokerage (page 12) Status Is an Ambiguous Signal Banker Reputations: Top third Middle third Bottom third Network Constraint (C) many ——— Structural Holes ——— few
  • Closure Creates a Reputation Cost for Misbehavior, Which Facilitates Trust and Collaboration Robert Jessica Strategic Leadership Delivering Value: The Social Capital of Closure (page 4) Situation A Robert New Acquaintance (no embedding) Robert Jessica Robert Jessica Situation B Robert Long-Time Colleague Situation C Robert Co-Member Group ("relational" embedding) ("structural" embedding) More connections allow more rapid communication, so poor behavior can be more readily detected and punished. Bureaucratic authority was the traditional engine for coordination in organizations (budget, head count). The new engine is reputation (e.g., eBay). In flattened-down organizations, leader roles are often ambiguous, so people need help knowing who to trust, and the boss needs help supervising her direct reports. Multi-point evaluation systems, often discussed as 360° evaluation systems, gather evaluative data from the people who work with an employee. These are "reputational" systems in that evaluations are the same data that define an employee's reputation in the company. In essence, reputation is the governance mechanism in social networks. Figure 3.1 in Brokerage and Closure (for discussion, see pages 105-111). See Appendix IX on network embedding in the theory of the firm.
  • Search Check out LIVE auctions on eBay. tips Search titles and descriptions Overall profile makeup ID card 222 positives. 203 are from unique users and count toward the final rating. dan (200) Member since Thursday, May 07, 1998 Summary of Most Recent Comments 3 neutrals. 3 are from users no longer registered. Past 7 days Past month Past 6 mo. Positive 5 84 Neutral 0 0 0 Negative Total 0 0 0 5 1 85 Bid Retractions 3 negatives. 3 are from unique users and count toward the final rating. 0 0 0 0 Auctions by dan Note: There are 3 comments that were converted to neutral because the commenting users are no longer registered. You can leave feedback for this user. Visit the Feedback Forum for more info on feedback profiles. If you are dan (200) , you can respond to comments in this Feedback Profile. Items 1-25 of 228 total = 1 = [2] [3] [4] [5] [6] [7] [8] [9] [10] (next page) User: chache@fyi.net (4) Date: Jan-04-01 09:36:46 PST Item: 508790896 Praise: probably the best seller on ebay. goes all out to make sure the buyer is happy! User: marywdwrth@aol.com (58) Date: Dec-31-00 16:02:19 PST Item: 512484383 Praise: item in perfect condition, great to deal with, quick service User: sararah1 (121) Date: Dec-30-00 13:20:51 PST Item: 512488662
  • About Don't Date Him Girl - contact us Thanks for Your Interest in DontDateHimGirl.com, an online community of powerful women from around the world who choose to exercise their rights to free speech on the Internet by boldly sharing their bad dating experiences with other women. This site has been the subject of international media attention from publications like the Sunday Times of London, The New York Times, the Wall Street Journal and the New York Post; major television networks such as CNN, MSNBC, Fox News and television shows like the Today Show, Dr. Phil and Montell Williams, not to mention a hot topic in the blogosphere, Take a look at what all the buzz in about by becoming a member today! You will find informative articles about dating and relationships; advice to help you make better decisions in finding a man you love; a live chat area where members can exchange experiences in real-time and of course, the postings of hundreds of thousands of women who are banding together to protect each other from having one more bad date! Men, in the spirit of fairness, you can participate in the forum as well by becoming a member. Join Now! EXCELLENT RESOURCES FOR WOMEN The links provided by below offer a wealth of information on many aspects of women's rights. These web sites are associated with organizations that, along with www.DontDateHimGirl.com, are part of a worldwide movement to advocate for and defend the rights of women around the world. We update these links periodically. Although we check these links often, sometimes links are outdated or no longer functioning. We apologize for any links that may no longer work. If you find any bad links, please send an e-mail to webmaster@dontdatehimgirl.com. http://dontdatehimgirl.com/about_us/index.html Name: enter your username Password: ********* LOGON remember password • become a member • forgot password • add a cheater CHECK OUT OUR NEW E-STORE Proceeds benefit The Women's Alliance and the National Coalition Against Censorship! BREAKING UP IS HARD
  • III. Network Closure as the Source: Echo Story (vs good behavior or closure bandwidth) Strategic Leadership Delivering Value: The Social Capital of Closure (page 13) Third parties selectively repeat information and enforcement, and so amplify relations to extremes of trust and distrust. See Section 4.1 in Brokerage and Closure, Appendix IV on susceptibility to gossip, Dunbar (1996) Grooming, Gossip, and the Evolution of Language. "Echo" vs "Bandwidth" versions of closure argument: more channels of communication create more frequent selective reinforcement. Third parties do not enhance information and protection so much as they create an echo that makes people feel more certain in their opinion of you. Bias in selecting third parties (balance mechanism) — Faced with a decision about whether to trust you, the other person (ego) turns to trusted contacts before less close contacts for information on you. Trusted contacts are likely to have views similar to ego’s, so they are likely to report accounts of you consistent with ego’s own view. A preference for trusted third parties means that ego draws a sample of information on you consistent with his or her predisposition toward you. Bias in what third parties say (etiquette mechanism) — It is polite in conversation to go along with the flow of sentiment being shared. We tend to share in conversations those of our facts consistent with the perceived predispositions of the people with whom we speak, and facts shared with other people are facts more likely to be remembered. The biased sample of facts shared in conversations becomes the population of information on, and so the reality of, the people discussed. For example (Higgans, 1992), an undergraduate subject is given a written description of a hypothetical person (Donald). The subject is asked to describe Donald to a second student who walks into the lab. The second person is a Quidnunc (KWID-nunk, from confederate who primes the conversation by leaking his predisposition toward Donald (“kinda likes” or “kinda dislikes” Donald). Latin "what now", to English in Subjects distort their descriptions of Donald toward the expressed predisposition. Positive predisposition elicits positive words 1709) - a person who seeks about Donald’s ambiguous characteristics and neglect of negative concrete characteristics. Negative predisposition elicits to know all the latest news or gossip. Example: I lowered my negative words about Donald’s ambiguous characteristics and neglect of positive concrete characteristics. voice when I noticed that Nancy, the office quidnunc, was standing In sum, echo has the other person (ego) in vicarious play with you in gossip relayed by third parties. The sample of your right next to my cubicle hoping to behavior to which ego is exposed is biased by etiquette to be consistent with ego’s predisposition toward you. The result is overhear what I was saying. that ego becomes ignorantly certain about you, and so more likely to trust or distrust you (as opposed to remaining undecided between the two extremes). Favorable opinion is amplified into trust. Doubt is amplified into distrust. The trust expected in strong relations is more likely and intense in relations embedded in strong third-party ties. The distrust expected in weak and negative relations is more likely and intense in relations embedded in strong third-party ties.
  • Lovegety From Wikipedia, the free encyclopedia Lovegety is a wireless-enabled, spontaneous matchmaking service that originated in Japan in 1998. Mr.Takeya Takafuji and his friends created Lovegety. Users enter their profile of interests into the device and when the device, with a limited wireless communications range, discovers a user with a “matching” profile, LoveGety notifies the user that their matched partner is nearby. Notification is done via device vibration. LoveGety was the inspiration for countless bluetooth-enabled matchmaking services for mobile phones, see Bluedating.
  • Detail on Gossip Creating Ignorant Certainty. Expect extreme opinions amplified by gossip in closed networks (regardless of the bandwidth focus on positive versus negative indirect connections through mutual contacts). GOSSIP (data filtered by etiquette) CREATES IGNORANT CERTAINTY Distribution of the stories known Opinion of Business Leader Strategic Leadership Delivering Value: The Social Capital of Closure (page 14) E Stories they know Extreme Positive Ego’s Initial Extreme Negative J Stories they share E E E E E E J E E E E E E E E E E E E E 1 E J E E E E E E E E 2 E E E J E E E E E 3 Distribution of the stories ego hears E J E E E E E E E 4 5 ... Ego’s sequence of conversations in which business leader is discussed For discussion, read the footnotes on pages 98-99 and 106 of Brokerage and Closure. For selected illustration from a team of employees driven into ignorant certainty, see Levy, "The Nut Island Effect" (2001, HBR). Several examples are briefly described in Chapter 4 of Brokerage and Closure. Confidence interval around ego’s opinion is the average datum, plus and minus the standard error, which is S . √N 2 is severely underestimated Variance S by the stories shared with ego. The number of observations N is increasing as ego hears more stories. So the confidence interval around ego’s opinion becomes tight, making ego feel certain, but only because etiquette has filtered out data inconsistent with ego’s opinion.
  • A. Stability from Year to Year B. Disappears Without Closure 4 3 2 2 3 4 1 Mean Correlation for Banker’s Reputation from this Year to Next (13-person subsample) Reputation Next Year (average evaluation by colleagues) 1 Bold line through white dots describes above average reputations (8.1 routine t-test). Dashed line through black dots describes reputations average and below (6.1 routine t-test). Analysts Bankers Reputation This Year (average evaluation by colleagues) banker Mean Number of Third Parties Connecting Banker with Colleagues This Year 10 or more 4 3 2 1 2 banker Figure 2.11 Closure Essential to Reputation Graph A plots analyst and banker reputations this year versus next. Squares are analysts (r = .55, t = 9.78), and circles are bankers (r = .61, t = 13.16). Graph B describes for the bankers subsample correlations between positive (above average) and negative (below average) reputations this year and next year. Adapted from Burt (2010:162, 166). From R. S. Burt, "The Network Structure of Advantage" (available at http://faculty.chicagobooth.edu/ronald.burt/research) 3 4 1
  • Implications for Managing Reputation Questions: When Closure When Closure Creates Bandwidth Creates Echo (most (e.g., Amazon, eBay) social networks) Your consistent behavior, on which others are informed. The bandwidth provided by a closed network enhances information distribution and consistency. Consistent stories circulating among them about your behavior. The echo produced by etiquette enhances story distribution and consistency in a closed network. 2. Therefore, who owns your reputation? Strategic Leadership Delivering Value: The Social Capital of Closure (page 24) 1. What makes your reputation persist? You do. It is defined directly and indirectly by your behavior. They do. It is defined by people gossiping about you. Reputation quickly decays in open networks. 3. So, what are the implications for effectively building reputation? Behave well and get the word out. Put a premium on projects, products, and services likely to be talked about. 4. How many reputations do you have? (Does the relevant network distribute or filter information?) One reputation, defined by your behavior. Variation can exist from imperfect information distribution or conflicting interests, but variation is resolved by finding the true, authentic you. Multiple, depending on gossip. You have as many reputations as there are groups in which you are discussed. The reputations can be similar, but they are generated and maintained separately. Table 2.4 in Burt, "Network Structure of Advantage" (2013 manuscript)
  • Appendix Materials
  • B. Yielding Performance Scores Higher than Peers A. Brokers Are More Likely to Detect & Articulate Good Ideas (r = -.58, t = -6.78, n = 85) (evaluation, compensation, promotion) Z-Score Residual Performance Average Z-Score Idea Value (r = -.80, t = -9.67, n = 54) Network Constraint many ——— Structural Holes ——— few Figure 2.3 Brokerage for Detecting and Developing Opportunities Graph A shows idea quality increasing with more access to structural holes. Circles are average scores on the vertical axis for a five-point interval of network constraint among supply-chain managers in a large electronics firm (Burt, 2004:382, 2005:92). Bold line is the vertical axis predicted by the natural logarithm of network constraint. Graph B shows performance increasing with more access to structural holes. Circles are average scores on the vertical axis for a five-point interval of network constraint within each of six populations (analysts, bankers, and managers in Asia, Europe, and North America; Burt, 2010:26, cf. Burt, 2005:56).
  • Figure 2.4 Network Brokers Tend To Be Recognized Leaders Constraint and status are computed from work discussion networks around twelve hundred managers in four organizations. A. In the formal organization B. And in the informal organization Most Senior Job Ranks (29.5 mean network constraint) 1% Next-Lower, Senior Ranks (41.9 mean constraint) r2 = .61 Next-Lower, Middle Ranks (56.4 mean constraint) Network Constraint many ——— Structural Holes ——— few Network Status (S) (Si = Σj zji Sj, divided by mean so average is 1.0) Percent of People within Each Level of Job Ranks 18% Network Constraint many ——— Structural Holes ——— few From R. S. Burt, "The Network Structure of Advantage" (available at http://faculty.chicagobooth.edu/ronald.burt/research)
  • Figure 2.9 Diagnostic Contingency in Three Organizations Z-Score Relative Compensation Network Constraint The One Other Division r = .09, t = 1.05, P = .30 Z-Score Relative Compensation Z-Score Relative Compensation Network Constraint Acquiring Management r = -.40, t = -4.92, P < .001 Acquired Management r = .11, t = 1.06, P = .29 Senior Men r = -.40 t = -5.56 P < .001 Network Constraint Early Promotion (in years) Z-Score Relative Compensation All But One Division of Firm r = -.36, t = -5.66, P < .001 C. Diversity Early Promotion (in years) B. Merger & Acquisition A. Leader Development Women and Junior Men r = .30 t = 3.38 P < .01 From R. S. Burt, "The Network Structure of Advantage" (available at http://faculty.chicagobooth.edu/ronald.burt/research)
  • 4 3 2 2 3 4 1 Mean Correlation for Banker’s Reputation from this Year to Next (13-person subsample) 1 Brokers (8): Y = .248 + .202 log(X), n = 894, t = 13.0 4 Other (J): Y = -.047 + .274 log(X), n = 897, t = 15.1 3 2 1 2 3 4 1 banker Mean Number of Third Parties Connecting People in the Networks around Banker’s Contacts this Year 10 or more banker Figure 2.13 Essential Closure Is Around Contacts, Maintaining the Reputations of Brokers and People in Closed Networks Vertical axis is same as in Figure 2.11B. Horizontal axis is average number of third party connections in the networks around banker's contacts (rounded to nearest whole number). Brokers are bankers with below-median network constraint this year. Regression lines in graph go through averages. Regression equations estimated from 894 year-to-year banker transitions. Test statistics are adjusted down for correlation between repeated observations of the same bankers using the "cluster" option in Stata. From R. S. Burt, "The Network Structure of Advantage" (available at http://faculty.chicagobooth.edu/ronald.burt/research)
  • 409 Who Talks To Whom 472 255 169 219 182 629 936 948 337 355 932 682 427 690 933 484 587 947 480 440 554 252 292 441 732 59 930 949 328 394 859 935 929 924 695 899 920 855 898 895 901 894 893 892 406 557 888 563 213 628 572 139 421 36 565 503 487 907 673 769 919 297 314 144 425 692 376 356 152 747 67 937 461 131 455 78 385 883 648 613 771 538 109 685 636 887 908 900 107 889 121 999 209 11 890 848 917 821 237 120 624 20 871 194 766 164 915 74 232 761 192 760 73 137 788 926 39 884 891 33 299 804 488 818 352 311 934 927 616 312 669 506 244 801 564 428 842 882 75 556 50 48 99 797 662 931 353 689 315 380 851 540 370 95 632 190 781 885 443 126 709 879 174 896 535 384 390 110 44 61 483 656 108 303 340 91 868 270 532 909 92 254 84 34 897 770 294 677 672 905 510 782 914 886 903 922 128 47 90 155 902 923 726 220 96 802 287 561 928 145 787 132 277 910 437 306 524 258 916 Nonrespondent 904 739 301 584 234 490 832 Respondent (reports to participant) 906 318 485 911 559 Senior Executive Team (not invited to survey) 921 743 381 913 Program Participant 912 188 426 Lines indicate frequent and substantive work contact (.15 ≤ connect ≤ 1.00) 143 321 469 233 925 172 68 387 175 105 641 69 330 432 372 324 594 434 23 918 684 98 803 223 72 55