Match!

The Process of Knowledge Transfer: A Diachronic Analysis of Stickiness☆

Published on May 1, 2000in Organizational Behavior and Human Decision Processes2.91
· DOI :10.1006/obhd.2000.2884
Gabriel Szulanski20
Estimated H-index: 20
(UPenn: University of Pennsylvania)
Cite
Abstract
Even though intrafirm transfers of knowledge are often laborious, time consuming, and difficult, current conceptions treat them as essentially costless and instantaneous. When acknowledged, difficulty is an anomaly in the way transfers are modeled rather than a characteristic feature of the transfer itself. One first step toward incorporating difficulty in the analysis of knowledge transfer is to recognize that a transfer is not an act, as typically modeled, but a process. This article offers a process model of knowledge transfer. The model identifies stages of transfer and factors that are expected to correlate with difficulty at different stages of the transfer. The general expectation is that factors that affect the opportunity to transfer are more likely to predict difficulty during the initiation phase, whereas factors that affect the execution of the transfer are more likely to predict difficulty during subsequent implementation phases. Measures of stickiness are developed for each stage of the transfer to explore the predictive power of different factors at different stages of the process. A cross-sectional analysis of primary data collected through a two-step survey of 122 transfers of organizational practices within eight firms illustrates the applicability of the model and suggests several issues for further research.
Figures & Tables
  • References (61)
  • Citations (1196)
Cite
References61
Newest
#1Marcie J. Tyre (MIT: Massachusetts Institute of Technology)H-Index: 9
#2Wanda J. Orlikowski (MIT: Massachusetts Institute of Technology)H-Index: 59
Cited By1196
Newest
#1C. Prem Sankar (UoK: University of Kerala)H-Index: 3
#2Drisya Alex Thumba (UoK: University of Kerala)
Last.K. Satheesh Kumar (UoK: University of Kerala)H-Index: 9
view all 5 authors...
#1Marina Latukha (SPbU: Saint Petersburg State University)H-Index: 5
#2Anna Veselova (SPbU: Saint Petersburg State University)H-Index: 1
#1Manami Suzuki (Hosei University)
#2Naoki Ando (Hosei University)H-Index: 6
Last.Hidehiko Nishikawa (Hosei University)H-Index: 2
view all 3 authors...
#1Hengqin Wu (HIT: Harbin Institute of Technology)H-Index: 2
#2Xiaolong Xue (GU: Guangzhou University)
Last.Xiaowei Luo (CityU: City University of Hong Kong)H-Index: 5
view all 6 authors...
View next paperThe Knowledge-Creating Company