Abstract: Recently, the use of web 2.0 tools has increased in
companies and public administration organisations. This
phenomenon, known as "Enterprise 2.0", has, de facto, modified
common organisational and operative practices. This has led
“knowledge workers” to change their working practices through the
use of Web 2.0 communication tools. Unfortunately, these tools have
not been integrated with existing enterprise information systems, a
situation that could potentially lead to a loss of information. This is
an important problem in an organisational context, because
knowledge of information exchanged within the organisation is
needed to increase the efficiency and competitiveness of the
organisation. In this article we demonstrate that it is possible to
capture this knowledge using collaboration processes, which are
processes of abstraction created in accordance with design patterns
and applied to new organisational operative practices.
Abstract: This paper presents an analytical framework for an
effective online personal knowledge management (PKM) of
knowledge workers. The development of this framework is prompted
by our qualitative research on the PKM processes and cognitive
enablers of knowledge workers in eight organisations selected from
three main industries in Malaysia. This multiple-case research
identifies the relationships between the effectiveness of four online
PKM processes: get/retrieve, understand/analyse, share, and connect.
It also establishes the importance of cognitive enablers that mediate
this relationship, namely, method, identify, decide and drive.
Qualitative analysis is presented as the findings, supported by the
preceded quantitative analysis on an exploratory questionnaire
survey.
Abstract: Through the course of this paper we define Business Case Management and its characteristics, and highlight its link to knowledge workers. Business Case Management combines knowledge and process effectively, supporting the ad hoc and unpredictable nature of cases, and coordinate a range of other technologies to appropriately support knowledge-intensive processes. We emphasize the growing importance of knowledge workers and the current poor support for knowledge work automation. We also discuss the challenges in supporting this kind of knowledge work and propose a novel approach to overcome these challenges.