팀원의 사회적 지위와 지식수준이 조언 네트워크 중심성에 미치는영향 및 분산교류 기억체계의 조절효과

With increasing complexity and specialization of knowledge and expertise, organizations have extensively utilized teams as a basic unit of structure for competitive advantages. Teams consists of members with varying degrees of expertise, and team members need to utilize other members’ expertise for collective tasks. This paper focuses on advice network centrality in teams by examining when and why a member turns to others for seeking advice. Specifically, we posit that teams can effectively utilize members’ expertise when expert members are situated at a central position in advice network. First, we argue that a member’s level of perceived expertise is positively related with advice network centrality. For example, a member may consider quality of expertise they receive when they seek advice from others, and thus, the member will approach to other members who are perceived as experts. Second, we argue that high status members are more likely to be in central positions in advice network. Status characteristic theory suggest that people tend to infer ability of others from social characteristics, such that they expect high performance from high status members and defer their view to the high status members (even when controlling their level of expertise). Further, we present a contingency model in which the effects of expertise level and social status depends on the team context (e.g., transactive memory system; TMS). Transactive memory system is defined as a shared mental model of knowing who knows what among team members. Under the high level of TMS, expertise will become a more salient and accessible cue to team members, and as a result, they will be more attentive to the expert members. Yet, the low level of TMS may cause disagreement about who knows what and suffer identifying expert members in teams. This leads non-expertise-related cues (e.g., social status) to be a more noticeable factor for members seeking advice. Therefore, we propose the following hypotheses with the theoretical model. H1: A member’s perceived level of expertise will be positively related with advice network centrality. H2: A member’s social status will be positively related with advice network centrality. H3: Transactive memory system will moderate the positive relationship between a member’s perceived level of expertise and advice network centrality, such that the relationship will be stronger when TMS is high than when it is low. H4: Transactive memory system will moderate the positive relationship between social status and advice network centrality, such that the relationship will be weaker when TMS is high than it is low. Using multi-wave survey data from 30 project teams with 130 members, we analyze our theoretical model with intercepts-and-slopes-as-outcomes modeling. The results show that team members’ perceived expertise level and social status have positive relationships with advice network centrality. We also found that the relationship between social status and advice network centrality is weakened when TMS is high. We discuss implications of these findings for research and practice.