We develop a method to assess the three indicators of transactive memory systems (TMS)—specialization, credibility, and coordination—through computer-aided text analysis. First, human coders assessed group transcripts for phrases representative of these indicators. From those phrases, we identified words that occurred frequently to develop a dictionary of TMS indicators. In total, we analyzed 262 groups composed of 1,091 individuals. Both the human-coded and dictionary-based assessments of TMS indicators are significantly related to a popular survey-based assessment of TMS. Our approach could be used to advance understanding of TMS by analyzing it in contexts where administering surveys is not feasible.
AustinJ. R. (2003). Transactive memory in organizational groups: The effects of content, consensus, specialization, and accuracy on group performance. Journal of Applied Psychology, 88(5), 866–878. https://doi.org/10.1037/0021-9010.88.5.866
2.
BachrachD. G.LewisK.KimY.PatelP. C.CampionM. C.ThatcherS. (2019). Transactive memory systems in context: A meta-analytic examination of contextual factors in transactive memory systems development and team performance. Journal of Applied Psychology, 104(3), 464–493. https://doi.org/10.1037/apl0000329
3.
BenoitK. (2018). Quanteda: Quantitative analysis of textual data. R package version 1.3.4. http://quanteda.io
4.
BoydR. L.AshokkumarA.SerajS.PennebakerJ. W. (2022). The development and psychometric properties of LIWC-22. University of Texas at Austin. https://www.liwc.app/
5.
CookJ.WallT. (1980). New work attitude measures of trust, organizational commitment and personal need non-fulfilment. Journal of Occupational Psychology, 53(1), 39–52. https://doi.org/10.1111/j.2044-8325.1980.tb00005.x
6.
DeChurchL. A.Mesmer-MagnusJ. R. (2010). The cognitive underpinnings of effective teamwork: A meta-analysis. Journal of Applied Psychology, 95(1), 32–53. https://doi.org/10.1037/a0017328
7.
De WeverB.SchellensT.ValckeM.Van KeerH. (2006). Content analysis schemes to analyze transcripts of online asynchronous discussion groups: A review. Computers & Education, 46(1), 6–28. https://doi.org/10.1016/j.compedu.2005.04.005
FettermanA. K.BoydR. L.RobinsonM. D. (2015). Power versus affiliation in political ideology: Robust linguistic evidence for distinct motivation-related signatures. Personality and Social Psychology Bulletin, 41(9), 1195–1206. https://doi.org/10.1177/0146167215591960
10.
FleissJ. L. (1971). Measuring nominal scale agreement among many raters. Psychological Bulletin, 76(5), 378–382. https://doi.org/10.1037/h0031619
11.
GuptaP.WoolleyA. W. (2018). Productivity in an era of multi-teaming: The role of information dashboards and shared cognition in team performance. Proceedings of the ACM on Human-Computer Interaction, 2(CSCW), 1–18. https://doi.org/10.1145/3274331
12.
HollingsheadA. B. (1998). Retrieval processes in transactive memory systems. Journal of Personality and Social Psychology, 74(3), 659–671. https://doi.org/10.1037/0022-3514.74.3.659
13.
HuY. Y.ParkerS. H.LipsitzS. R.ArriagaA. F.PeyreS. E.CorsoK. A.RothE. M.YuleS. J.GreenbergC. C. (2016). Surgeons’ leadership styles and team behavior in the operating room. Journal of the American College of Surgeons, 222(1), 41–51. https://doi.org/10.1016/j.jamcollsurg.2015.09.013
14.
KanawattanachaiP.YooY. (2007). The impact of knowledge coordination on virtual team performance over time. MIS Quarterly, 31, 783–808. https://doi.org/10.2307/25148820
15.
KrippendorffK. (1980). Validity in content analysis. In MochmannE. (Ed.), Computerstrategien für die Kommunikationsanalyse (pp. 69–112). Campus. http://repository.upenn.edu/asc_papers/291
16.
KushJ. (2019). Conceptual and measurement issues for transactive memory systems: The indicators of TMS. Group Dynamics: Theory, Research, and Practice, 23(2), 104–123. https://doi.org/10.1037/gdn0000101
17.
LandisJ. R.KochG. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310
18.
LeBretonJ. M.SenterJ. L. (2008). Answers to 20 questions about interrater reliability and interrater agreement. Organizational Research Methods, 11(4), 815–852. https://doi.org/10.1177/1094428106296642
19.
LewisK. (2003). Measuring transactive memory systems in the field: Scale development and validation. Journal of Applied Psychology, 88(4), 587–604. https://doi.org/10.1037/0021-9010.88.4.587
20.
LewisK. (2004). Knowledge and performance in knowledge-worker teams: A longitudinal study of transactive memory systems. Management Science, 50(11), 1519–1533. https://doi.org/10.1287/mnsc.1040.0257
21.
LewisK.HerndonB. (2011). Transactive memory systems: Current issues and future research directions. Organization Science, 22(5), 1254–1265. https://doi.org/10.1287/orsc.1110.0647
22.
LiangD. W.MorelandR.ArgoteL. (1995). Group versus individual training and group performance: The mediating role of transactive memory. Personality and Social Psychology Bulletin, 21(4), 384–393. https://doi.org/10.1177/0146167295214009
23.
MackenzieC. F.XiaoY.HorstR. (2004). Video task analysis in high performance teams. Cognition, Technology & Work, 6(3), 139–147. https://doi.org/10.1007/s10111-004-0155-1
24.
MartindaleC. (1990). The clockwork muse: The predictability of artistic change. Basic Books. https://doi.org/10.2307/430964
25.
MathieuJ. E.WolfsonM. A.ParkS.LucianoM. M.Bedwell-TorresW. L.RamsayP. S.KlockE. A.TannenbaumS. I. (2021). Indexing dynamic collective constructs using computer-aided text analysis: Construct validity evidence and illustrations featuring team processes. Journal of Applied Psychology, 107(4), 533–559. https://doi.org/10.1037/apl0000856
26.
McAllisterD. J. (1995). Affect- and cognition-based trust as foundations for interpersonal cooperation in organizations. Academy of Management Journal, 38(1), 24–59. https://journals.aom.org/doi/abs/10.5465/256727
27.
MellJ.van KnippenbergD.van GinkelW. P.HeugensP. (2014). Whose brain to pick? Boundary spanning and transactive memory in inter-group knowledge integration. Academy of Management Proceedings, 2014, 12519. https://doi.org/10.5465/ambpp.2014.205
28.
MladenicD.GrobelnikM. (1999). Feature selection for unbalanced class distribution and Naïve Bayes. In BratkoI.DžeroskiS. (Eds.), Machine learning, proceedings of the 16th international conference (pp. 258–267). Morgan Kaufmann Publishers. https://dl.acm.org/doi/10.5555/645528.657649
PandeyS.PandeyS. K. (2017). Applying natural language processing capabilities in computerized textual analysis to measure organizational culture. Organizational Research Methods, 22(3), 765–797. https://doi.org/10.1177/1094428117745648
31.
PennebakerJ. W.BoothR. J.BoydR. L.FrancisM. E. (2015). Linguistic inquiry and word count: LIWC2015. Pennebaker Conglomerates. www.LIWC.net
32.
RenY.ArgoteL. (2011). Transactive memory systems 1985–2010: An integrative framework of key dimensions, antecedents, and consequences. The Academy of Management Annals, 5(1), 189–229. https://doi.org/10.5465/19416520.2011.590300
33.
ShortJ. C.BrobergJ. C.CogliserC. C.BrighamK. H. (2010). Construct validation using computer-aided text analysis (CATA): An illustration using entrepreneurial orientation. Organizational Research Methods, 13(2), 320–347. https://doi.org/10.1177/1094428109335949
34.
WegnerD. M. (1987). Transactive memory: A contemporary analysis of the group mind. In MullenB.GoethalsG. R. (Eds.), Theories of group behavior (pp. 185–208). Springer. https://doi.org/10.1007/978-1-4612-4634-3_9
35.
WegnerD. M.GiulianoT.HertelP. T. (1985). Cognitive interdependence in close relationships. In IckesW. (Ed.), Compatible and incompatible relationships (pp. 253–276). Springer. https://doi.org/10.1007/978-1-4612-5044-9_12
WeickK. E.RobertsK. H. (1993). Collective mind in organizations: Heedful interrelating on flight decks. Administrative Science Quarterly, 38(3), 357–381. https://doi.org/10.2307/2393372
38.
WeingartL. R. (2012). Studying dynamics within groups. In NealeM. A.MannixE. A. (Eds.), Looking back, moving forward: A review of group and team-based research (Vol. 15, pp. 1–25). Emerald Publishing. https://doi.org/10.1108/S1534-0856(2012)15
39.
WeingartL. R.OlekalnsM.SmithP. L. (2004). Quantitative coding of negotiation behavior. International Negotiation, 9(3), 441–456. https://doi.org/10.1163/1571806053498805
40.
WoodrumE. (1984). “Mainstreaming” content analysis in social science: Methodological advantages, obstacles, and solutions. Social Science Research, 13(1), 1–19. https://doi.org/10.1016/0049-089X(84)90001-2
41.
ZhangY.OlenickJ.ChangC. H.KozlowskiS. W.HungH. (2018). TeamSense: Assessing personal affect and group cohesion in small teams through dyadic interaction and behavior analysis with wearable sensors. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2(3), 1–22. https://doi.org/10.1145/3264960
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