2. Academy of Management, New Orleans, 2004 1 Taking a crack at measuring faultlines Sherry M.B. Thatcher (University of Arizona) Katerina Bezrukova (Rutgers University) Karen A. Jehn (Leiden University)

3. Academy of Management, New Orleans, 2004 2 Agenda Interactive Exercise Why? –Importance of faultlines vs. other composition measures How? –What we did Huh? –Problems we ran into (and how we fixed them) Oh, that! –Issues that journal reviewers are likely to raise

4. Academy of Management, New Orleans, 2004 3 Interactive exercise 1 2 6 5 4 3

5. Academy of Management, New Orleans, 2004 4 Interactive exercise In breaking the group into subgroups, what characteristics did you look at? How homogeneous are the subgroups? What assumptions did you make when breaking the group into subgroups?

6. Academy of Management, New Orleans, 2004 5 Why? Mixed effects of diversity and demography studies Focus on more than one attribute at a time Takes into account interdependence among attributes

7. Academy of Management, New Orleans, 2004 6 How? From Diversity to Faultlines Step 1: Picturing what we need to measure ♀♀P♀♀P ♀♀P♀♀P ♀♀P♀♀P ♀♀P♀♀P ♀♀P♀♀P ♀♀P♀♀P Educ. Race Sex ♂♂P♂♂P ♀♀H♀♀H ♂♂P♂♂P ♀♀H♀♀H ♂♂P♂♂P ♀♀H♀♀H Educ. Race Sex Group A: Strong FaultlineGroup B: Weak Faultlines  H = High school, P = PhD, W = White, B = Black, M = Male, F = Female HWM PBF HWM HBF PBM PWF

8. Academy of Management, New Orleans, 2004 7 How? Step 2: Understanding diversity formulas 3 2 1 [1/n  (X i - X j ) 2 ] 1/2 ] Individual-level categorical and interval variables. Relational demography /individual dissimilarity score (Tsui & O’Reilly, 1989). SD Group-level interval variables. Coefficient of variation (Allison, 1978). (1 –  Pi   Group-level categorical variables. Index of heterogeneity (Blau, 1977; Bantel & Jackson, 1989); Diversity or entropy index (Teachman, 1980; Ancona & Caldwell, 1992). x

9. Academy of Management, New Orleans, 2004 8 How? Step 3:Creating a faultline strength formula Faultline strength – Clustering Algorithm based on Euclidean distance formula (Thatcher, Jehn, & Zanutto, 2003) –x ijk = the value of the j th characteristic of the i th member of subgroup k –x j = the overall group mean of characteristic j –x jk = the mean of characteristic j in subgroup k –n g k = the number of members of the k th subgroup (k=1,2) under split g –the faultline strength = the maximum value of Fau g over all possible splits g=1,2,…S.

10. Academy of Management, New Orleans, 2004 9 Measuring Faultlines 0.463 (strongest split is AC, BD but AB, CD is also a strong split) Weak (1 align; 4 ways) 0.996 (strongest split is AB, CD) Very Strong (4 align; 1 way) 0.688 (strongest split is AC, BD) Strong (3 align; 2 ways) 0.557 ( strongest split is AB, CD, but BC, AD is also close ) Weak (1 align; 3 ways) 0None FAU ALGORITHM based on Euclidean distance formula FAULTLINE STRENGTH/ L & M

11. Academy of Management, New Orleans, 2004 10 How? Revisiting Step 1: Faultline Distance Faultline distance reflects how far apart the subgroups are from each other Age Education Tenure Age Education Tenure 3055 M.S.Ph.D. 1122 55 Ph.D. 22 21 B.A. 3  Group B: Closer TogetherGroup A: Farther Apart

12. Academy of Management, New Orleans, 2004 11 Faultline Distance (cont’d) Faultline distance - the Euclidean distance between the two sets of averages where centroid (vector of means of each variable) for subgroup 1 = ( ), centroid for subgroup 2 = ( ). Group faultline score Fau = Strength (Fau g ) x Distance (D g )

13. Academy of Management, New Orleans, 2004 12 Faultlines Strength and Distance, and Group Faultlines Scores MemberAgeRaceGenderTenureFunctionEducation Team 10.80572.93342.3634 165112635 23711237 350102634 43611437 54610137 Team 20.83042.02651.6828 16121617 234101015 34510415 44721917 53710115 Faultline Strength Faultline Distance Group Faultlines Score

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16. Academy of Management, New Orleans, 2004 15 Rescaling Considerations Theory driven approach –to use SME’s judgments to weight characteristics Empirical approach –to view participants’ responses as a “true” measure of faultlines Statistical approach –to use standard deviations

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23. Academy of Management, New Orleans, 2004 22 SAS Faultline Calculation (Version 1.0, July 26, 2004) 1.WHAT THIS CODE DOES faultline strength and distance for groups of size 3 to 16 (two sets: incl and excl 1-person subgroups). 2.WHAT WE ASSUME ABOUT THE DATA a comma-separated data text file (save as.csv file). dummy variables for categorical vars. no missing values group ID variable (groups are numbered from 1 to n) 3.WHAT WE ASSUME ABOUT THE RESCALING FACTORS rescaling factors must be specified for each variable rescaling factors must be specified in a comma-separated text file (save as.csv file).

24. Academy of Management, New Orleans, 2004 23 SAS Faultline Calculation (Version 1.0, July 26, 2004): Cont’d 4. HOW TO RUN THE CODE –download the SAS code and data files into C:\Faultline\FL_code\FL_Code_parameters.txt –go to the C:\Faultline\FL_Code directory and double click on FL_Code_1_0.sas –right click the mouse and select “Submit All” 5. HOW TO MODIFY THE INPUT PARAMETERS –all user inputs are specified in the file C:\Faultline\FL_Code\FL_Code_parameters.txt. –keep exact names of files.

25. Academy of Management, New Orleans, 2004 24 Huh? Problems we ran into (and how we fixed them) Group size Number of possible subgroups Subgroups of size “1” Calculating the overall faultline score Measuring faultline distance for categorical variables Rescaling

26. Academy of Management, New Orleans, 2004 25 Oh That! Issues that journal reviewers have raised Rescaling (influence on results) –solution: rerun analyses Importance of distance component –solution: explain it better Perceptual faultlines = actual faultlines? –solution: explain to the reviewers that we didn’t have this data

27. Academy of Management, New Orleans, 2004 26 Advantages of Fau Measure allows continuous and categorical variables unlimited number of variables theoretically unlimited group size flexible enough to allow for different rescaling

28. Academy of Management, New Orleans, 2004 27 Future Research & Work in Progress Testing the theory in experimental settings Faultlines, coalitions, conflict, group identity and leadership profiles Temporal effects of faultlines Testing the theory in organizational settings Consistency matters! The Effects of Group and Organizational Culture on the Faultline-Outcomes Link Testing the theory in international settings Peacekeeping and Ethnopolitical conflict A quasi-experimental field study in ethnic conflict zones (i.e., Crimea, Sri Lanka, Burundi and Bosnia)

29. Academy of Management, New Orleans, 2004 28 Thank you very much for coming Any questions?