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knowledge retention and transfer:how libraries manage employees leaving…
knowledge retention and transfer:how libraries manage employees leaving and joining
background
includes
embeded in activities of organizations
knowledge generated within libraries
Knowledge management in libraries
enables information
knowledge to grow
flow and create value
focuses on
academic libraries
need for km in libraries
knowledge sharing beheaviour
Types of knowledge
Explicit
is
systamatic
can be
articulated
codified
stored
tacit
is
learning by doing
difficult to transfer
knowledge retention
involves
capturing knowledge in organization
subdiciple of
knowledge management
knowledge transfer
means
expertise
knowledge skills
example: outgoing to current employees, incoming employees
activities associated
communication
translation
conversion
filtering
rendering
Methodology
focuses on
qualitative analysis of open-end responses
purpose was to reach wide pool of academic libraries
Involves
data analysis
data needs to be entered in excel spreadsheet
three kinds of codings were carried out
open coding
axial coding
selective coding
findings
contains
demographic data
majority of respondents had maasters degree
discussion
importatnt for
knowledge retention of outgoing employees
includes
documentation
training
digital repositary
decision upport capabilities of enterprise content management systems
information
becomes
complex
dispersed
strategic approach
decision support technology
background
conceptualization of ECM
identification of
content requirements
ECM offers
operational benifits
tactical benifits
strategic benefits
related work
includes
enterprise resouorce planning(ERP)
Customer relationship management(CRM)
Supply chain management(SCM)
conceptual Modedl and hypothesis
appropriate information technology
effects
organizatinonal performance
includes
productivity
quality
probability
customer satisfaction
Identification phase and capture activity
specify two routines
decision recognition
Routine initiates
ds process by
recognizing problems
oppurtunities
crisis
development phase and organise activity
search routine
decision maker
engages various activities
decision routine
solutions idetified in
search routine arer adapted to fit specific problem sistuation
selection phase and process activity
empirical study
measurement
carried out at
large public reasearch universityx for
capturing
organising
managing diverse content assets
data
conducted using
questionaire
sample covered 28 departments
used "key format" approach
results
measurement model
accessed through
reliability
indicator
reliability
convergent validity
discriminant validit
structural model
accessed using variance at
level of significance of path coefficients
discussion
implications for practise
scope and rational for ECM
ECM aggregates
organizatinal information
ECM use facitilities problem assessment
contibutions to theory
adapt to growing volume
digital content and real time information
knowledge life cycle (KLC) on semantic web
KLC changes
coeventinal ways of thinking
semantic has its web
well structured data, semantic metadata
which makes easy for computers
different stages
include
integration
representattion
interconnection
reasoning
retrieving
validation
introduction
KLC is most effective concept in
New generation knowlege management (NGKM)
allows to perform production of NKGM
first generation concerns with
distributuion
sharing
of existing knowledge
production of new technology
relies on
artificial intelligence
semantic web is not a
seperate web but
extension of current one
KLC in next generation knowlege management
life cycle of knowledge is
continum regime of
knowledge process
divided into
three fundamental phases
production
knowledge validation
knowledge integration
theoritical foundadtion is
complex adaptive system theory(CAS theory)
Importance of studying KLC on semantic web
makes it posiible
for AI to manage knowledge on web
contrary to knowledge in
human organizations
semantic web is
created
processed
stored
transfered
KLC on semantic web
knowledge representation
main purpose is
changed on semanted web
traditionally,web content is
formatted for
human readers
rather than programs
knowledge interconnection
builds web between data
todays web is not web of data but
a web of computers or applications
examples:uniform resource identifier and Name space
Knowledge reasoning
strength lies in
ability to knowledge reason
difficult for today's web
because of
lacking metadata and rules
knowledge retrieving
reyrieved with high precision
examples:XQL,XQUERY,X-PATH
knowledge validation
semantic web may be
redundant
out-of data
incorrect
or disorted
necessary to validate the result
knowledge integration
knowledge should be
validated and integrated
has three kinds of integration tools
message oriented middleware(MOM)
Application programing interface
example:ADO,.NET.
Technologies to integrate knowledge with bussiness process