A Multidimensional Network Approach to Studying Team Members' Information Seeking From Human and Digital Knowledge Sources in Consulting Firms

The goal of this study is to understand how consultants' information seeking from human and digital knowledge sources is influenced by their relationships with both types of knowledge sources and the characteristics of the knowledge domain in which information seeking takes place. Grounded on and extending transactive memory theory, this study takes a multidimensional approach to predict consultants' information seeking based on expertise recognition, source accessibility, peer information-seeking behaviors, knowledge complexity, and codifiability. Using data collected from 110 consultants across 9 project teams from 2 multinational consulting firms, this study found that consultants' information seeking from human knowledge sources was mostly driven by the expertise and accessibility level of their team members, whereas their information seeking from digital knowledge repositories was strongly influenced by how much information the digital knowledge source had and whether colleagues with whom they had strong social communication ties were seeking information from the digital source. Finally, knowledge complexity had a negative influence on consultants' information seeking from digital knowledge repositories, but knowledge codifiability had no significant effects on information seeking from either knowledge source. This study demonstrates the importance and viability of using a multidimensional network approach to advancing transactive memory theory to study consultants' information-seeking practices.