All in due time: The development of trust in distributed groups

1. All in due time: The development of trust in distributed groups Jeanne Wilson The College of William & Mary School of Business Administration March 17. 2003

2. Trust in Distributed Groups Overall research program objective: Understand interpersonal relations (trust) at a distance Motivation • Paradox of trust in distributed groups • Competing theoretical explanations • Inadequacy of existing theory

3. Distributed Groups Groups in which some or all of the members do not work in the same physical location • 52% of large companies use geographically distributed teams (deLisser, 1999) • Collaborative work in a virtual arrangement has been cited as a top workforce trend in the next 10 years (Kemske, 1998)

4. Trust Trust - willingness to be vulnerable based on positive expectations of the intentions or behavior of others (Mayer, Davis & Schoorman, 1995; Rousseau, Sitkin, Burt & Camerer, 1998) Cognitive trust - beliefs about reliability and dependability (McAllister, 1995) Affective trust - beliefs about reciprocated care and concern (McAllister, 1995)

5. Overall program plan Study 1 - Lab experiment, test of existing theory (Wilson, Straus & McEvily, 1999) Study 2 - Field study, focuses on distributed groups in context, develops a broader theory of interpersonal relations at a distance Common denominators: looking at trust over time in distributed groups

6. Study 1: Competing theoretical perspectives Cues Filtered Out -Computer-mediated communication reduces social context cues and leads to depersonalization (Kiesler, Siegel & McGuire, 1984; Daft, Lengel & Trevino, 1987) Social-identity Deindividuation - Group identity is the most salient cue computer-mediated groups have; this leads to social self-categorization (Lea & Spears, 1992) Social Information Processing -All groups are motivated to develop social relationships. It takes longer in computer-mediated groups because there is less social information per message (Walther, 1992; 1995)

7. Study 1: Sample and Task • 52, 3-person groups (participants randomly assigned to group, groups randomly assigned to condition) • Each group met three times, with the following cycle of tasks:  narrow down a list of stocks to 3 that members would research(together or separately)  spend tokens on researched stocks (cooperating or defecting)

8. Four conditions FFF EEE EFF FEE

9. Cognitive Trust The interaction of Condition X Time was significant (F6,98 = 3.69, p < .01).

10. Affective Trust The interaction of Condition X Time was significant (F6,98 = 3.09, p < .01).

11. Cooperation Time by condition interaction was significant using Generalized Estimating Equations - for categorical variables over time (B = .90, Z = 3.95, p < .0001).

12. Reliance Condition effect was significant (B = 1.18, Z = 2.25, p < .05); Time by Condition interaction was marginally significant (B = .53, Z = 1.73, p < .10)

13. Conclusions • Results support social information processing predictions (trust develops more slowly in computer mediated groups) • Starting condition matters • Prescriptions for practice depend on the nature of the group  length of time  malleability of the task

14. Limitations • Student teams lack a “shadow of the future” or structural assurance (which are likely to affect the development of trust in organizational groups)

15. Inadequacy of existing theories • All of the theories about development in distributed groups are about media effects • Distributed groups differ from co-located groups on more dimensions than the technology they use to communicate  Distance  Familiarity  Face-to-face contact  Identity

16. What we know about distance The original law of propinquity (Newcomb, 1956) Physical proximity Frequency of interaction Similarity Liking

17. The Site • Large bank in the midwest • Corporate assets: $30 billion • Provides trust, investment, and retirement services • Corporate group transitioning to a new team structure: some teams co-located, some not

18. 78 Teams Investments Relationship Manager NTRC Account Manager Daily Valuation Treasury Consultant Global Accounts Info. Delivery Analyst RPS Consultant

19. Design Quantitative: XPO X1 X2 X3 X4 X5 X6 O X6 Qualitative: Three teams: varying on distance, familiarity, amount of face-to-face contact • interviewing all members of the teams once a month regarding expectations, trust, violations, attributions, and other team processes that might be affecting trust. • attending all (formal) team meetings

20. What predicts trust between team members at month 3? From HLM analyses:

21. Extras

22. Full 3-way longitudinal model Level 1 model - dyadic variables over time (trust and communication) Level 2 model - variation among dyads within a group (familiarity and distance) Level 3 model - variation between groups (group identity)

23. Results from Level 1 analysis • trust between team members is increasing over time (t = 42.46, p < .001) • the amount of communication between team members has an effect on the development of trust over time (t = 19.31, p < .01)

24. Level 2 & 3: Intercepts as outcomes • familiar dyads do start with higher levels of trust (t = 4.49, p < .001) • trust between individual team members is marginally higher in groups with higher levels of group identity (t = 2.12, p < .10).

25. Level 2 & 3: slopes as outcomes • Group identity does not influence the rate of trust development between individual members of the teams (t = 0.67, ns). • Dyads who are familiar with each other at the outset have a slower rate of growth in trust development than dyads who are not familiar with each other (t = -2.98, p < .01).

26. Descriptive Statistics

27. Means and standard deviations over time