Knowledge Management (KM) has become a central theme in today’s business environment and a commonly cited source of competitive advantage. This paper argues that one of the main drivers of knowledge-related organizational problems is the dispersed nature of organizational knowledge. In today’s global economy, much of economic activity in and between firms is based on dispersed knowledge workers (DW). Therefore, developing tools to support KM in distributed environments is becoming a major challenge. On the basis of literary reviews and on field research consisting of 6 explorative case studies (Corso et al, 2003 a; Corso et al, 2003 b) and a survey on 82 Italian firms (with a response rate of 43%), a research investigation framework has been developed and refined. It analyses four groups of variables and their relationships: Dispersed Workers Profiles, KM Systems (KMS), and Performances. On the basis of the work DWs do, it is possible to group Dispersed Workers into three main classes: sales force (47%), maintenance people (35%) and consultants (18%). Building on this survey preliminary results, we will develop three explicative case studies in order to deeply understand the cause-effect links between DW Profiles and KMS.
Dispersed Workers Profiles and KMS: Towards an Evolution?
MARTINI, ANTONELLA;PELLEGRINI, LUISA;
2004-01-01
Abstract
Knowledge Management (KM) has become a central theme in today’s business environment and a commonly cited source of competitive advantage. This paper argues that one of the main drivers of knowledge-related organizational problems is the dispersed nature of organizational knowledge. In today’s global economy, much of economic activity in and between firms is based on dispersed knowledge workers (DW). Therefore, developing tools to support KM in distributed environments is becoming a major challenge. On the basis of literary reviews and on field research consisting of 6 explorative case studies (Corso et al, 2003 a; Corso et al, 2003 b) and a survey on 82 Italian firms (with a response rate of 43%), a research investigation framework has been developed and refined. It analyses four groups of variables and their relationships: Dispersed Workers Profiles, KM Systems (KMS), and Performances. On the basis of the work DWs do, it is possible to group Dispersed Workers into three main classes: sales force (47%), maintenance people (35%) and consultants (18%). Building on this survey preliminary results, we will develop three explicative case studies in order to deeply understand the cause-effect links between DW Profiles and KMS.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
