Presentation on theme: "Why Should I Trust You? Predictors of Interpersonal Trust in a Knowledge Transfer Context Daniel Z. Levin Rutgers University Rob Cross University of Virginia."— Presentation transcript:
Why Should I Trust You? Predictors of Interpersonal Trust in a Knowledge Transfer Context Daniel Z. Levin Rutgers University Rob Cross University of Virginia Lisa C. Abrams IBM Institute for Knowledge-based Organizations
Theoretical Background Knowledge creation and transfer are critical for organizations (Argote 1999; Kogut & Zander 1992, 1996; Spender 1996) Relationships—especially trust—are key to the success of knowledge transfer (Levin, Cross, & Abrams 2002; Tsai & Ghoshal 1998; Uzzi 1997) Yet only limited systematic empirical work on predictors of interpersonal trust, in general and especially in this context
Research Question: What Factors Predict a Knowledge Seeker’s Trust in the Benevolence and Competence of a Knowledge Source?
A Multi-Level Approach: 3 Categories of Trust Predictors Relationship “Alter” “Ego” Knowledge Seeker Source
Survey Methods Two-stage, critical-incident, egocentric network survey Three companies: U.S. drug co., Canadian oil & gas co., U.K. bank 127 respondents reported on 4 relationships (n=508), response rate=48% Controls: formal structure; seeker’s own expertise Hierarchical linear modeling for nested data
Competence Shared Vision Shared Language Unavailable Source Discreet Source Younger Seeker Interaction Effect Significant Predictors of Trust Benevolence Strong Ties Shared Vision Shared Language Discreet Source Receptive Source Younger Seeker Hi-Tenure Seeker vs.
Competence Shared Vision Shared Language Unavailable Source Discreet Source Younger Seeker + Interaction Effect Variables in All 3 Categories Were Statistically Significant Benevolence Strong Ties Shared Vision Shared Language Discreet Source Receptive Source Younger Seeker Hi-Tenure Seeker
(1) Benevolence-based Trust Was Easier to Predict than Competence-based Trust In terms of the number of significant predictors In terms of the variance accounted for –R-squared for benevolence =.66 –R-squared for competence =.48
(2) Trust Is Not Set in Stone… Malleable features: –Discreet source –Shared vision –Shared language Stable and visible features: –Formal structure –Homophily (same age & gender) Big Effect No Effect X
(3) …But Attitudes in the Trust Realm May Solidify Over Time Knowledge seekers evaluate alter’s behavior to find “clues for competence” Clues = discreet & busy (i.e., unavailable) Interaction effect for division tenure: The more tenure that knowledge seekers have… the more they rely on the “clues for competence”
Contribution… …to practice: Building trust is a feasible and inexpensive way to improve the flow of knowledge …to social network and trust lit.: Theoretical benefits to examining different types of trust …to org. learning and knowledge lit.: Better understanding of factors underlying the success of trust and knowledge transfer