The Learning Curve of Knowledge Workers in a Computing Call Cente

Youngsoo KIM, Singapore Management University
Ramayya Krishnan
Linda Argote


We analyze learning and knowledge transfer in a computing call center. The information technology (IT) technical services provided by call centers are characterized by constant changes in relevant knowledge and a wide variety of support requests. Under this IT problem-solving context, we analyze the learning curve relationship between problem-solving experience and performance enhancement. Based on data collected from a university computing call center consisting of different types of consultants, our empirical findings indicate that (a) the learning effect—as measured by the reduction of average resolution time—occurs with experience, (b) knowledge transfer within a group occurs among lower-level consultants utilizing application-level knowledge (as opposed to technical-level knowledge), and (c) knowledge transfers across IT problem types. These estimates of learning and knowledge transfer contribute to the development of an empirically grounded understanding of IT knowledge workers’ learning behavior. The results also have implications for operational decisions about the staffing and problem-solving strategy of call centers.