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Alavi & Leidner/Knowledge Management
MIS Quarterly Vol. 25 No. 1, pp. 107-136/March 2001 107
MISQ REVIEW
REVIEW: KNOWLEDGE MANAGEMENT AND
KNOWLEDGE MANAGEMENT SYSTEMS:
CONCEPTUAL FOUNDATIONS AND
RESEARCH ISSUES1, 2
By: Maryam Alavi
John and Lucy Cook Chair of Information
Technology
Goizueta Business School
Emory University
Atlanta, GA 30322
U.S.A.
Maryam_Alavi@bus.Emory.edu
Dorothy E. Leidner
Texas Christian University
Fort Worth, Texas 76129
U.S.A., and
INSEAD
77305 Fontainebleau
FRANCE
dorothy.leidner@insead.fr
Abstract
Knowledge is a broad and abstract notion that has
defined epistemological debate in western philo-
sophy since the classical Greek era. In the past
1Richard Watson was the accepting senior editor for this
paper.
2MISQ Review articles survey, conceptualize, and
synthesize prior MIS research and set directions for
future research. For more details see
http://www.misq.org/misreview/announce.html
few years, however, there has been a growing
interest in treating knowledge as a significant
organizational resource. Consistent with the
interest in organizational knowledge and knowl-
edge management (KM), IS researchers have
begun promoting a class of information systems,
referred to as knowledge management systems
(KMS). The objective of KMS is to support crea-
tion, transfer, and application of knowledge in
organizations. Knowledge and knowledge man-
agement are complex and multi-faceted concepts.
Thus, effective development and implementation
of KMS requires a foundation in several rich
literatures.
To be credible, KMS research and development
should preserve and build upon the significant
literature that exists in different but related fields.
This paper provides a review and interpretation of
knowledge management literatures in different
fields with an eye toward identifying the important
areas for research. We present a detailed process
view of organizational knowledge management
with a focus on the potential role of information
technology in this process. Drawing upon the
literature review and analysis of knowledge man-
agement processes, we discuss several important
research issues surrounding the knowledge man-
agement processes and the role of IT in support of
these processes.
Alavi & Leidner/Knowledge Management
108 MIS Quarterly Vol. 25 No. 1/March 2001
Keywords: Knowledge management, knowledge
management systems, research issues in knowl-
edge management, organizational knowledge
management, knowledge management review
ISRL Categories: HA, A103, DD07, IB03
In post-capitalism, power comes from
transmitting information to make it pro-
ductive, not from hiding it.
Drucker 1995
Introduction
A knowledge-based perspective of the firm has
emerged in the strategic management literature
(Cole 1998; Spender 1996a, 1996b; Nonaka and
Takeuchi 1995). This perspective builds upon and
extends the resource-based theory of the firm ini-
tially promoted by Penrose (1959) and expanded
by others (Barney 1991; Conner 1991; Wernerfelt
1984).
The knowledge-based perspective postulates that
the services rendered by tangible resources
depend on how they are combined and applied,
which is in turn a function of the firm’s know-how
(i.e., knowledge). This knowledge is embedded in
and carried through multiple entities including
organization culture and identity, routines, poli-
cies, systems, and documents, as well as indivi-
dual employees (Grant 1996a, 1996b; Nelson and
Winter 1982; Spender 1996a, 1996b). Because
knowledge-based resources are usually difficult to
imitate and socially complex, the knowledge-
based view of the firm posits that these knowledge
assets may produce long-term sustainable
competitive advantage. However, it is less the
knowledge existing at any given time per se than
the firm’s ability to effectively apply the existing
knowledge to create new knowledge and to take
action that forms the basis for achieving compe-
titive advantage from knowledge-based assets. It
is here that information technologies may play an
important role in effectuating the knowledge-
based view of the firm. Advanced information
technologies (e.g., the Internet, intranets, extra-
nets, browsers, data warehouses, data mining
techniques, and software agents) can be used to
systematize, enhance, and expedite large-scale
intra- and inter-firm knowledge management.
Although the concept of coding, storing, and trans-
mitting knowledge in organizations is not new—
training and employee development programs,
organizational policies, routines, procedures, re-
ports, and manuals have served this function for
years (Alavi and Leidner 1999)—organizational
and managerial practice has recently become
more knowledge-focused. For example, bench-
marking, knowledge audits, best practice transfer,
and employee development point to the realization
of the im portance of o rganizational knowledg e and
intangible assets in general (Grant 1996a, 1996b;
Spender 1996a, 1996b). Given the importance of
organizational knowledge, our objective is to
synthesize the relevant and knowledge-centered
work from multiple disciplines that in our view
contribute to and shape our understanding of
knowledg e management and knowledg e manage-
ment systems in organizations.
The paper is organized as follows: the next
section presents a review of the management
literature on knowledge and the firm. This section
provides a comprehensive summary of alternative
views of knowledge and knowledge taxonomies
and their i mplications f or knowledge management.
The following section adopts the process view of
knowledge management and presents this view in
detail with an eye toward identifying the potential
role of information technologies in the various
stages of the knowledge management process. A
broader organizational perspective on knowledge
management research is then provided by dis-
cussing important research themes that emerge
from the review of the literature. The final section
provides a summary and presents the discussion
of the four general conclusions of our work.
Knowledge and the Firm:
An Overview and
Basic Concepts
The question of defining knowledge has occupied
the minds of philosophers since the classical
Alavi & Leidner/Knowledge Management
MIS Quarterly Vol. 25 No. 1/March 2001 109
Greek era and has led to many epistemological
debates. It is unnecessary for the purposes of this
paper to engage in a debate to probe, question, or
reframe the term knowledge, or discover the
“universal truth,” from the perspective of ancient or
modern philosophy. This is because such an
understanding of knowledge was neither a deter-
minant factor in building the knowledge-based
theory of the firm nor in triggering researcher and
practitioner interest in managing organizational
knowledge. It is, however, useful to consider the
manifold views of knowledge as discussed in the
information technology (IT), strategic manage-
ment, and organizational theory literature. This will
enable us to uncover some assumptions about
knowledge that underlie organizational knowledge
management processes and KMS. We will begin
by considering definitions of knowledge.
The Hierarchical View of Data,
Information, and Knowledge
Some authors, most notably in IT literature,
address the question of defining knowledge by
distinguishing among knowledge, informati on, and
data. The assumption seems to be that if knowl-
edge is not something that is different from data or
information, then there is nothing new or
interesting about knowledge management (Fahey
and Prusak 1998). A commonly held view with
sundry minor variants is that data is raw numbers
and facts, information is processed data, and
knowledge is authenticated information (Dreske
1981; Machlup 1983; Vance 1997). Yet the pre-
sumption of a hierarchy from data to information to
knowledge with each varying along some dimen-
sion, such as context, usefulness, or interpre-
tability, rarely survives scrupulous evaluation.
What is key to effectively distinguishing between
information and knowledge is not found in the
content, structure, accuracy, or utility of the sup-
posed information or knowledge. Rather, knowl-
edge is information possessed in the mind of
individuals: it is personalized information (which
may or may not be new, unique, useful, or accu-
rate) related to facts, procedures, concepts,
interpretations, ideas, observations, and judg-
ments.
Tuomi (1999) makes the iconoclastic argument
that the often-assumed hierarchy from data to
knowledge is actually inverse: knowledge must
exist before information can be formulated and
before data can be measured to form information.
As such, “raw data” do not exist—even the most
elementary piece of “data” has already been
influenced by the thought or knowledge processes
that led to its identification and collection. Tuomi
argues that knowledge exists which, when
articulated, verbalized, and structured, becomes
information which, when assigned a fixed repre-
sentation and standard interpretation, becomes
data. Critical to this argument is the fact that
knowledge does not exist outside of an agent (a
knower): it is indelibly shaped by one’s needs as
well as one’s initial stock of knowledge (Fahey
and Prusak 1998; Tuomi 1999). Knowledge is
thus the result of cognitive processing triggered by
the inflow of new stimuli. Consistent with this
view, we posit that information is converted to
knowledge once it is processed in the mind of
individuals and knowledge becomes information
once it is articulated and presented in the form of
text, graphics, words, or other symbolic forms. A
significant implication of this view of knowledge is
that for individuals to arrive at the same under-
standing of data or information, they must share a
certain knowledge base. Another important impli-
cation of this definition of knowledge is that
systems designed to support knowledge in organi-
zations may not appear radically different from
other forms of information systems, but will be
geared toward enabling users to assign meaning
to information and to capture some of their knowl-
edge in information and/or data.
Alternative Perspectives
on Knowledge
Knowledge is defined as a justified belief that
increases an entity’s capacity for effective action
(Huber 1991; Nonaka 1994). Knowledge may be
viewed from several perspectives (1) a state of
mind, (2) an object, (3) a process, (4) a condition
of having access to information, or (5) a capability.
Alavi & Leidner/Knowledge Management
110 MIS Quarterly Vol. 25 No. 1/March 2001
Knowledge has been described as “a state or fact
of knowing” with knowing being a condition of
“understanding gained through experience or
study; the sum or range of what has been per-
ceived, discovered, or learned” (Schubert et al.
1998). The perspective on knowledge as a state
of mind focuses on enabling individuals to expand
their personal knowledge and apply it to the
organization’s needs. A second view defines
knowledge as an object (Carlsson et al. 1996;
McQueen 1998; Zack 1998a). This perspective
posits that knowledge can be viewed as a thing to
be stored and manipulated (i.e., an object)
Alternatively, knowledge can be viewed as a pro-
cess of simultaneously knowing and acting
(Carlsson et al. 1996; McQueen 1998; Zack
1998a). The process perspective focuses on the
applying of expertise (Zack 1998a). The fourth
view of knowledge is that of a condition of access
to information (McQueen 1998). According to this
view, organizational knowledge must be organized
to facilitate access to and retrieval of content. This
view may be thought of as an extension of the
view of knowledge as an object, with a special
emphasis on the accessibility of the knowledge
objects. Finally, knowledge can be viewed as a
capability with the potential for influencing future
action (Carlsson et al. 1996). Watson (1999)
builds upon the capability view by suggesting that
knowledge is not so much a capability for specific
action, but the capacity to use information;
learning and experience result in an ability to inter-
pret information and to ascertain what information
is necessary in decision making.
These different views of knowledge lead to
different perceptions of knowledge management
(Carlsson et al. 1996). If knowledge is viewed as
an object, or is equated with information access,
then knowledge management should focus on
building and managing knowledge stocks. If
knowledge is a process, then the implied knowl-
edge management focus is on knowledge flow
and the processes of creation, sharing, and
distribution of knowledge. The view of knowledge
as a capability suggests a knowledge manage-
ment perspective centered on building core
compet encies, understanding t he strategic a dvan-
tage of know-how, and creating intellectual capital.
The major implication of these various concep-
tions of knowledge is that each perspective
suggests a different strategy for managing the
knowledge and a different perspective of the role
of systems in support of knowledge management.
Table 1 summarizes the various views of knowl-
edge just discussed and their implications for
knowledge management and knowledge manage-
ment systems. The perspective relied upon most
heavily in this article is that implied in the distinc-
tion of knowledge from data and information,
closely related to the perspective of knowledge as
a state of mind.
Summary of Knowledge
Perspective
Three major points emerge from the above
discussion: (1) A great deal of emphasis is given
to understanding the difference among data,
information, and knowledge and drawing implica-
tions from the difference. (2) Because knowledge
is personalized, in order for an individual’s or a
group’s knowledge to be useful for others, it must
be expressed in such a manner as to be inter-
pretable by the receivers. (3) Hoards of informa-
tion are of little value; only that information which
is actively processed in the mind of an individual
through a process of reflection, enlightenment, or
learning can be useful.
Taxonomies of Knowledge
Drawing on the work of Polanyi (1962, 1967),
Nonaka (1994) explicated two dimensions of
knowledge in organizations: tacit and explicit.
Rooted in action, experience, and involvement in
a specific context, the tacit dimension of knowl-
edge (henceforth referred to as tacit knowledge)
is comprised of both cognitive and technical
elements (Nonaka 1994). The cognitive element
refers to an individual’s mental models consisting
of mental maps, beliefs, paradigms, and view-
points. The technical component consists of
concrete know-how, crafts, and skills that apply to
a specific context. An example of tacit knowledge
is knowledge of the best means of approaching a
particular customer—using flattery, using a hard
sell, using a no-nonsense approach. The explicit
dimension of knowledge (henceforth referred to as
explicit knowledge) is articulated, codified, and
communicated in symbolic form and/or natural
language. An example is an owner’s manual
accompanying the purchase of an electronic
product. The manual contains knowledge on the
appropriate operation of the product.
Alavi & Leidner/Knowledge Management
MIS Quarterly Vol. 25 No. 1/March 2001 111
Table 1. Knowledge Perspectives and Their Implications
Perspectives
Implications for
Knowledge
Management (KM)
Implications for
Knowledge Manage-
ment Systems (KMS)
Knowledge vis-à-
vis data and
information
Data is facts, raw numbers.
Information is processed/
interpreted data.
Knowledge is personalized
information.
KM focuses on ex-
posing individuals to
potentially useful infor-
mation and facilitating
assimilation of informa-
tion
KMS will not appear
radically different from
existing IS, but will be
extended toward helping
in user assimilation of
information
State of mind Knowledge is the state of
knowing and understanding.
KM involves enhancing
individual’s learning
and understanding
through provision of
information
Role of IT is to provide
access to sources of
knowledge rather than
knowledge itself
Object Knowledge is an object to
be stored and manipulated.
Key KM issue is
building and managing
knowledge stocks
Role of IT involves
gathering, storing, and
transferring knowledge
Process Knowledge is a process of
applying expertise.
KM focus is on
knowledge flows and
the process of
creation, sharing, and
distributing knowledge
Role of IT is to provide
link among sources of
knowledge to create
wider breadth and depth
of knowledge flows
Access to
information
Knowledge is a condition of
access to information.
KM focus is organized
access to and retrieval
of content
Role of IT is to provide
effective search and
retrieval mechanisms for
locating relevant
information
Capability Knowledge is the potential
to influence action.
KM is about building
core competencies
and understanding
strategic know-how
Role of IT is to enhance
intellectual capital by sup-
porting development of
individual and organiza-
tional competencies
Knowledge can also be viewed as existing in the
individual or the collective (Nonaka 1994).
Individual knowledge is created by and exists in
the individual whereas social knowledge is
created by and inherent in the collective actions of
a group. Both Nonaka and others (e.g., Spender
1992, 1996a, 1995b) rely heavily on the tacit-
explicit, individual-collective knowledge distinc tion
but do not provide a comprehensive explanation
as to the interrelationships among the various
knowledge-types. One potentially problematic
aspect in the interpretation of this classification is
the assumption that tacit knowledge is more valu-
able than explicit knowledge; this is tantamount to
equating an inability to articulate knowledge with
its worth. Few, with the exception of Bohn (1994),
venture to suggest that explicit knowledge is more
valuable than tacit knowledge, a viewpoint that if
accepted might favor a technology enabled knowl-
edge management process (technology being
used to aid in explicating, storing, and dissemin-
ating knowledge).
Alavi & Leidner/Knowledge Management
112 MIS Quarterly Vol. 25 No. 1/March 2001
Whether tacit or explicit knowledge is the more
valuable may indeed miss the point. The two are
not dichotomous states of knowledge, but
mutually dependent and reinforcing qualities of
knowledge: tacit knowledge forms the back-
ground necessary for assigning the structure to
develop and interpret explicit knowledge (Polyani
1975). The inextricable linkage of tacit and
explicit knowledge suggests that only individuals
with a requisite level of shared knowledge can
truly exchange knowledge: if tacit knowledge is
necessary to the understanding of explicit knowl-
edge, then in order for Individual B to understand
Individual A’s knowledge, there must be some
overlap in their underlying knowledge bases (a
shared knowledge space) (Ivari and Linger 1999;
Tuomi 1999). However, it is precisely in applying
technology to increase “weak ties” (i.e., informal
and casual contacts among individuals) in organi-
zations (Pickering and King 1995), and thereby
increase the breadth of knowledge sharing, that IT
holds promise. Yet, absent a shared knowledge
space, the real impact of IT on knowledge
exchange is questionable. This is a paradox that
IT researchers have somewhat eschewed, and
that organizational researchers have used to
question the application of IT to knowledge
management. To add to the paradox, the very
essence of the knowledge management challenge
is to amalgamate knowledge across groups for
which IT can play a major role. What is most at
issue is the amount of contextual information
necessary for one person or group’s knowledge to
be readily understood by another.
It may be argued that the greater the shared
knowledge space, the less the context needed for
individuals to share knowledge within the group
and, hence, the higher the value of explicit
knowledge and the greater the value of IT applied
to knowledge management. On the other hand,
the smaller the existing shared knowledge space
in a group, the greater the need for contextual
information, the less relevant will be explicit
knowledge, and hence the less applicable will be
IT to knowledge management.
Tacit knowledge has received greater interest and
attention than has explicit knowledge, and yet the
former is not alone in providing both benefits and
challenges to organizations. Explicit knowledge
may pose a particular challenge related to an
assumption of legitimacy by virtue of being
recorded (Jordan and Jones 1997). This could
lead to decision makers favoring explicit knowl-
edge, at the expense of contradictory tacit
knowledge, because it may be viewed as more
legitimized and, hence, justifiable. Moreover,
given the ephemeral nature of some knowledge,
explicating knowledge may result in a rigidity and
inflexibility, which would impede, rather than
improve, performance.
The tacit-explicit knowledge classification is widely
cited, although sundry other knowledge classi-
fications exist that eschew the recondite subtleties
of the tacit-explicit dimension. Some refer to
knowledge as declarative (know-about or knowl-
edge by acquaintance [Nolan Norton 1998]),
procedural (know-how), causal (know-why),
conditional (know-when), and relational (know-
with) (Zack 1998c). A pragmatic approach to
classifying knowledge simply attempts to identify
types of knowledge that are useful to organiza-
tions. Examples include knowledge about custo-
mers, products, processes, and competitors,
which can include best practices, know-how and
heuristic rules, patterns, software code, business
process es, and models ; architectures, technology,
and business frameworks; project experiences
(proposals, work plans, and reports); and tools
used to implement a process such as checklists
and surveys (KPMG 1998b).
An understanding of the concept of knowledge
and knowledge taxonomies is important because
theoretical developments in the knowledge
management area are influenced by the distinc-
tion among the different types of knowledge.
Furthermore, the knowledge taxonomies dis-
cussed here can inform the design of knowledge
management systems by calling attention to the
need for support of different types of knowledge
and the flows among these different types.
Knowledge management may provide an oppor-
tunity for extending the scope of IT-based knowl-
edge provision to include the different knowledge
types summarized in Table 2.
Alavi & Leidner/Knowledge Management
MIS Quarterly Vol. 25 No. 1/March 2001 113
Table 2. Knowledge Taxonomies and Examples
Knowledge Types Definitions Examples
Tacit
Cognitive tacit:
Technical tacit:
Knowledge is rooted in actions,
experience, and involvement in
specific context
Mental models
Know-how applicable to specific
work
Best means of dealing with specific
customer
Individual’s belief on cause-
effect relationships
Surgery skills
Explicit Articulated, generalized knowledge Knowledge of major customers in a
region
Individual Created by and inherent in the
individual
Insights gained from completed
project
Social Created by and inherent in collective
actions of a group
Norms for inter-group
communication
Declarative Know-about What drug is appropriate for an
illness
Procedural Know-how How to administer a particular drug
Causal Know-why Understanding why the drug works
Conditional Know-when Understanding when to prescribe
the drug
Relational Know-with Understanding how the drug
interacts with other drugs
Pragmatic Useful knowledge for an
organization
Best practices, business
frameworks, project experiences,
engineering drawings, market
reports
Knowledge Management
in Organizations
The recent interest in organizational knowledge
has prompted the issue of managing the knowl-
edge to the organization’s benefit. Knowledge
management refers to identifying and leveraging
the collective knowledge in an organization to help
the organization compete (von Krogh 1998).
Knowledge management is purported to increase
innovativeness and responsiveness (Hackbarth
1998). A recent survey of European firms by
KPMG Peat Marwick (1998b) found that almost
half of the companies reported having suffered a
significant setback from losing key staff with 43%
experiencing impaired client or supplier relations
and 13% facing a loss of income because of the
departure of a single employee. In another sur-
vey, the majority of organizations believed that
much of the knowledge they needed existed
inside the organization, but that identifying that it
existed, finding it, and leveraging it remained
problematic (Cranfield University 1998). Such
problems maintaining, locating, and applying
knowledge have led to systematic attempts to
manage knowledge.
According to Davenport and Prusak (1998), most
knowledge management projects have one of
three aims: (1) to make knowledge visible and
show the role of knowledge in an organization,
mainly through maps, yellow pages, and hypertext
Alavi & Leidner/Knowledge Management
114 MIS Quarterly Vol. 25 No. 1/March 2001
tools; (2) to develop a knowledge-intensive culture
by encouraging and aggregating behaviors such
as knowledge sharing (as opposed to hoarding)
and proactively seeking and offering knowledge;
(3) to build a knowledge infrastructure—not only a
technical system, but a web of connections among
people given space, time, tools, and encourage-
ment to interact and collaborate.
Knowledge management is largely regarded as a
process involving various activities. Slight discre-
pancies in the delineation of the processes appear
in the literature, namely in terms of the number
and labeling of processes rather than the under-
lying concepts. At a minimum, one considers the
four basic processes of creating, storing/retrieving,
transferring, and applying knowledge. These
major processes can be subdivided, for example,
into creating internal knowledge, acquiring exter-
nal knowledge, storing knowledge in documents
versus storing in routines (Teece 1998) as well as
updating the knowledge and sharing knowledge
internally and externally. We will return to the
knowledge management processes in the frame-
work section and consider the role of IT within
each process.
Knowledge Management Systems
Knowledge management systems (KMS) refer to
a class of information systems applied to
managing organizational knowledge. That is, they
are IT-based systems developed to support and
enhance the organizational processes of knowl-
edge creation, storage/retrieval, transfer, and
application. While not all KM initiatives involve an
implementation of IT, and admonitions against an
emphasis on IT at the expense of the social and
cultural facets of KM are not uncommon (Daven-
port and Prusak 1998; Malhotra 1999; O’Dell and
Grayson 1998), many KM initiatives rely on IT as
an important enabler. While IT does not apply to
all of the issues of knowledge management, it can
support KM in sundry ways. Examples include
finding an expert or a recorded source of knowl-
edge using online directories and searching
databases; sharing knowledge and working
together in virtual teams; access to information on
past projects; and learning about customer needs
and behavior by analyzing transaction data
(KPMG 1998a), among others. Indeed, there is
no single role of IT in knowledge management just
as there is no single technology comprising KMS.
Reviewing the literature discussing applications of
IT to organizational knowledge management
initiatives reveals three common applications:
(1) the coding and sharing of best practices,
(2) the creation of corporate knowledge direc-
tories, and (3) the creation of knowledge net-
works. One of the most common applications is
internal benchmarking with the aim of transferring
internal best practices (KPMG 1998a; O’Dell and
Grayson 1998). For example, an insurance com-
pany was faced with the commoditization of its
market and declining profits. The company found
that applying the best decision making expertise
via a new underwriting process supported by a
knowledge management system enabled it to
move into profitable niche markets and, hence, to
increase income (Davenport and Prusak 1998).
Another common application of knowledge
management is the creation of corporate direc-
tories, also referred to as the mapping of internal
expertise. Because much knowledge in an organi-
zation remains uncodified, mapping the internal
expertise is a potentially useful application of
knowledge management (Ruggles 1998). One
survey found that 74% of respondents believed
that their organization’s best knowledge was
inaccessible and 68% thought that mistakes were
reproduced several times (Gazeau 1998). Such
perception of the failure to apply existing knowl-
edge is an incentive for mapping internal
expertise.
A third common application of knowledge man-
agement systems is the creation of knowledge
networks (Ruggles 1998). For example, when
Chrysler reorganized from functional to platform-
based organizational units, they realized quickly
that unless the suspension specialists could
communicate easily with each other across plat-
form types, expertise would deteriorate. Chrysler
formed Tech Cul, bringing people together
virtually and face-to-face to exchange and build
their collective knowledge in each of the specialty
areas. In this case, the knowledge management
Alavi & Leidner/Knowledge Management
MIS Quarterly Vol. 25 No. 1/March 2001 115
effort was less focused on mapping expertise or
benchmarking than it was on bringing the experts
together so that important knowledge was shared
and amplified. Providing online forums for com-
munication and discussion may form knowledge
networks. Buckman Laboratories uses an online
interactive forum where user comments are
threaded in conversational sequence and indexed
by topic, author, and date. This has reportedly
enabled Buckman to respond to the changing
basis of competition that has evolved from merely
selling products to solving customers’ chemical
treatment problems (Zack 1998a). In another
case, Ford found that just by sharing knowledge,
the development time for cars was reduced from
36 to 24 months, and through knowledge sharing
with dealers, the delivery delay reduced from 50 to
15 days (Gazeau 1998).
Summary: Knowledge and the Firm
Information systems designed to support and aug-
ment organizational knowledge management
need to complement and enhance the knowledge
management activities of individuals and the
collectivity. To achieve this, the design of infor-
mation systems should be rooted in and guided by
an understanding of the nature and types of
organizational knowledge. Different perspectives
on knowledge and various knowledge taxonomies
were discussed earlier. These discussions high-
light the importance of assessing and under-
standing an organization’s knowledge position and
its existing intellectual resources. Such an under-
standing is needed for formulating a knowledge
management strategy and in analyzing the role of
information technology in facilitating knowledge
management (discussed in the next section). In
the information systems (IS) field, it has been
common to design systems primarily focused on
the codified knowledge (that is, explicit organiza-
tional knowledge). Management reporting sys-
tems, decision support systems, and executive
support systems have all focused on the collection
and dissemination of this knowledge type.
Knowledge management systems may provide an
opportunity for extending the scope of IT-based
knowledge provision to include the different
knowledge forms and types shown in Table 2. We
are not suggesting that IT applied to the KM
efforts of a given organization must provide the
means of capturing all types of knowledge men-
tioned; the specific types of knowledge forming
the substance of an IT will depend upon an
organization’s context. We are suggesting, how-
ever, that IT as applied to KM need not be
constrained to certain types of knowledge,
because the advances in communication and
information technologies enable greater possi-
bilities than existed with previous classes of
information systems.
While the preponderance of knowledge manage-
ment theory stems from strategy and organiza-
tional theory research, the majority of knowledge
management initiatives involve at least in part, if
not to a significant degree, information technology.
Yet little IT research exists on the design, use, or
success of systems to support knowledge
management. The next section will examine the
four basic knowledge management processes and
the role that IT may play in each process.
Organizational Knowledge
Management Processes:
A Framework for Analysis
of the Role of an
Information System
In this section, we develop a systematic frame-
work that will be used to further analyze and
discuss the potential role of information techno-
logies in organizational knowledge management.
This framework is grounded in the sociology of
knowledge (Berger and Luckman 1967; Gurvitch
1971; Holzner and Marx 1979) and is based on
the view of organizations as social collectives and
“knowledge systems.” According to this frame-
work, organizations as knowledge systems consist
of four sets of socially enacted “knowledge
processes”: (1) creation (also referred to as
construction), (2) storage/retrieval, (3) transfer,
and (4) application (Holzner and Marx 1979;
Pentland 1995). This view of organizations as
knowledge systems represents both the cognitive
and social nature of organizational knowledge and
Alavi & Leidner/Knowledge Management
116 MIS Quarterly Vol. 25 No. 1/March 2001
its embodiment in the individual’s cognition and
practices as well as the collective (i.e., organiza-
tional) practices and culture. These processes do
not represent a monolithic set of activities, but an
interconnected and intertwined set of activities, as
explained later in this section.
Knowledge Creation
Organizational knowledge creation invo lves devel-
oping new content or replacing existing content
within the organization’s tacit and explicit knowl-
edge (Pentland 1995). Through social and
collaborative processes as well as an individual’s
cognitive processes (e.g., reflection), knowledge
is created, shared, amplified, enlarged, and
justified in organizational settings (Nonaka 1994).
This model views organizational knowledge crea-
tion as involving a continual interplay between the
tacit and explicit dimensions of knowledge and a
growing spiral flow as knowledge moves through
individual, group, and organizational levels. Four
modes of knowledge creation have been iden-
tified: socialization, externalization, internaliza-
tion, and combination (Nonaka 1994). The sociali-
zation mode refers to conversion of tacit
knowledge to new tacit knowledge through social
interactions and shared experience among
organizational members (e.g., apprenticeship).
The combination mode refers to the creation of
new explicit knowledge by merging, categorizing,
reclassifying, and synthesizing existing explicit
knowledge (e.g., literature survey reports). The
other two modes involve interactions and con-
version between tacit and explicit knowledge.
Externalization refers to converting tacit knowl-
edge to new explicit knowledge (e.g., articulation
of best practices or lessons learned). Internali-
zation refers to creation of new tacit knowledge
from explicit knowledge (e.g., the learning and
understanding that results from reading or
discussion).
The four knowledge creation modes are not pure,
but highly interdependent and intertwined. That
is, each mode relies on, contributes to, and
benefits from other modes. For example, the
socialization mode can result in creation of new
knowledge when an individual obtains a new
insight triggered by interaction with another. On
the other hand, the socialization mode may
involve transferring existing tacit knowledge from
one member to another through discussion of
ideas. New organizational knowledge per se may
not be created, but only knowledge that is new to
the recipient. The combination mode in most
cases involves an intermediate step—that of an
individual drawing insight from explicit sources
(i.e., internalization) and then coding the new
knowledge into an explicit form (externalization).
Finally, internalization may consist of the simple
conversion of existing explicit knowledge to an
individual’s tacit knowledge as well as creation of
new organizational knowledge when the explicit
source triggers a new insight.
Figure 1 illustrates the interplay among Nonaka’s
knowledge creation modes, and hence may be
useful in interpreting relationships between the
four modes.
In Figure 1, each arrow represents a form of
knowledge creation. The arrows labeled A
represent externalization; the arrows labeled B
represent internalization; the arrows labeled C
represent socialization; and the arrows labeled D
represent combination.
It may be useful to consider the conditions and
environments that facilitate new knowledge crea-
tion. Nonaka and Konno (1998) suggest that the
essential question of knowledge creation is
establishing an organization’s “ba” (defined as a
common place or space for creating knowledge).
Four types of ba corresponding to the four modes
of knowledge creation discussed above are
identified: (1) originating ba, (2) interacting ba,
(3) cyber ba, and (4) exercising ba (Nonaka and
Konno 1998). Originating ba entails the sociali-
zation mode of knowledge creation and is the ba
from which the organizational knowledge creation
process begins. Originating ba is a common place
in which individuals share experiences primarily
through face-to-face interactions and by being at
the same place at the same time. Interacting ba
is associated with the externalization mode of
knowledge creation and refers to a space where
tacit knowledge is converted to explicit knowledge
and shared among individuals through the pro-
cess of dialogue and collaboration. Cyber ba
refers to a virtual space of interaction and corres-
Alavi & Leidner/Knowledge Management
MIS Quarterly Vol. 25 No. 1/March 2001 117
Storage (document,
e-mail, intranet…)
Individual A’s
Tacit Knowledge
Individual B’s
Tacit Knowledge
C
A
B
Individual A’s
Explicit Knowledge
Storage (document,
e-mail, intranet…)
Individual B’s
Explicit Knowledge
A
B
Legend: Each arrow represents a form of knowledge creation.
A
B
D
A—Externalization; B—Internalization; C—Socialization;
D—Combination
A
B
Storage (document,
e-mail, intranet…)
Individual A’s
Tacit Knowledge
Individual B’s
Tacit Knowledge
C
A
B
Individual A’s
Explicit Knowledge
Storage (document,
e-mail, intranet…)
Individual B’s
Explicit Knowledge
A
B
Legend: Each arrow represents a form of knowledge creation.
A
B
D
A—Externalization; B—Internalization; C—Socialization;
D—Combination
A
B
Figure 1. Knowledge Creation Modes
ponds to the combination mode of knowledge
creation. Finally, exercising ba involves the
conversion of explicit to tacit knowledge through
the internalization process. Thus, exercising ba
entails a space for active and continuous indivi-
dual learning. Understanding the characteristics
of various ba and the relationship with the modes
of knowledge creation is important to enhancing
organizational knowledge creation. For example,
the use of IT capabilities in cyber ba is advocated
to enhance the efficiency of the combination mode
of knowledge creation (Nonaka and Konno 1998).
Data warehousing and data mining, documents
repositories, and software agents, for example,
may be of great value in cyber ba.
We further suggest that considering the flexibility
of modern IT, other forms of organizational ba and
the corresponding modes of knowledge creation
can be enhanced through the use of various forms
of information systems. For example, information
systems designed for support of collaboration,
coordination, and communication processes, as a
component of the interacting ba, can facilitate
teamwork and thereby increase an individual’s
contact with other individuals. Electronic mail and
group support systems have been shown to
increase the number of weak ties in organizations.
This in turn can accelerate the growth of knowl-
edge creation (Nonaka 1994). Intranets enable
exposure to greater amounts of on-line organiza-
tional information, both horizontally and vertically,
than may previously have been the case. As the
level of information exposure increases, the inter-
nalization mode of knowledge creation, wherein
individuals make observations and interpretations
of information that result in new individual tacit
knowledge, may increase. In this role, an intranet
Alavi & Leidner/Knowledge Management
118 MIS Quarterly Vol. 25 No. 1/March 2001
can support individual learning (conversion of
explicit knowledge to personal tacit knowledge)
through provision of capabilities such as computer
simulation (to support learning-by-doing) and
smart software tutors.
Computer-mediated communication may increase
the quality of knowledge creation by enabling a
forum for constructing and sharing beliefs, for
confirming consensual interpretation, and for
allowing expression of new ideas (Henderson and
Sussman 1997). By providing an extended field
for interaction among organizational members for
sharing ideas and perspectives, and for esta-
blishing dialog, information systems may enable
individuals to arrive at new insights and/or more
accurate interpretations than if left to decipher
information on their own. Boland et al. (1994)
provide a specific example of an information
system called Spider that provides an environ-
ment for representing, exchanging, and debating
different individual perspectives. The system
actualizes an extended field in which “assump-
tions are surfaced and questioned, new const ructs
emerge and dialog among different perspectives
is supported” (Boland et al. 1994, pp. 467). As
such, the quality and frequency of the knowledge
creation is improved.
Knowledge Storage/Retrieval
Empirical studies have shown that while organi-
zations create knowledge and learn, they also
forget (i.e., do not remember or lose track of the
acquired knowledge) (Argote et al. 1990; Darr et
al. 1995). Thus, the storage, organization, and re-
trieval of organizational knowledge, also referred
to as organizational memory (Stein and Zwass
1995; Walsh and Ungson 1991), constitute an
important aspect of effective organizational knowl-
edge management. Organizational memory
includes knowledge residing in various c omponent
forms, including written documentation, structured
information stored in electronic databases, codi-
fied human knowledge stored in expert systems,
documented organizational procedures and pro-
cesses and tacit knowledge acquired by indivi-
duals and networks of individuals (Tan et al.
1999).
Similar to the knowledge creation process
described in the previous section, a distinction
between individual and organizational memory
has been made in the literature. Individual mem-
ory is developed based on a person’s observa-
tions, experiences, and actions (Argyris and
Schön 1978; Nystrom and Starbuck 1981;
Sanderlands and Stablein 1987). Collective or
organizational memory is defined as “the means
by which knowledge from the past, experience,
and events influence present organizational
activities” (Stein and Zwass 1995, p. 85). Organi-
zational memory extends beyond the individual’s
memory to include other components such as
organizational cultur e, transformat ions (production
processes and work procedures), structure (formal
organizational roles), ecology (physical work
setting) and information archives (both internal
and external to the organization) (Walsh and
Ungson 1991).
Organizational memory is classified as semantic
or episodic (El Sawy et al. 1996; Stein and Zwass
1995). Semantic memory refers to general, explicit
and articulated knowledge (e.g., organizational
archives of annual reports), whereas episodic
memory refers to context-specific and situated
knowledge (e.g., specific circumstances of organi-
zational decisions and their outcomes, place, and
time). Memory may have both positive and nega-
tive potential influences on behavior and perfor-
mance. On the positive side, basing and relating
organizational change in past experience facili-
tates implementation of the change (Wilkins and
Bristow 1987). Memory also helps in storing and
reapplying workable solutions in the form of stan-
dards and procedures, which in turn avoid the
waste of organizational resources in replicating
previous work.
On the other hand, memory has a potential nega-
tive influence on individual and organizational
performance. At the individual level, memory can
result in decision-making bias (Starbuck and Hed-
berg 1977). At the organizational level, memory
may lead to maintaining the status quo by rein-
forcing single loop learning (defined as a process
of detecting and correcting errors) (Argyris and
Schön 1978). This could in turn lead to stable,
consistent organizational cultures that are resis-
tant to change (Denison and Mishra 1995).
Alavi & Leidner/Knowledge Management
MIS Quarterly Vol. 25 No. 1/March 2001 119
Despite the concerns about the potential con-
straining role of organizational memory, there is a
positive perspective on the influence of IT-enabled
organizational memory on the behavior and
performance of individuals and organizations.
Advanced computer storage technology and
sophisticated retrieval techniques, such as query
languages, multimedia databases, and database
management systems, can be effective tools in
enhancing organizational memory. These tools
increase the speed at which organizational
memory can be accessed. Weiser and Morrison
(1998) give the example of AI-STARS, a project
memory system at DEC (Digital Equipment
Corporation) that combines such information as
bulletin board postings, product release state-
ments, service manuals, and e-mail messages to
enable rapid access to product information for
assisting customer problems. Product memory
can be facilitated with corporate intranets, so that
product and pricing changes can be immediately
noted in the system instead of having brochures
reprinted. This in turn avoids the lag time resulting
from the time a change occurs to the time when
the sales personnel become aware of the change
(Leidner 1998).
Groupware enables organizations to create intra-
organizational memory in the form of both struc-
tured and unstructured information and to share
this memory across time and space (Vanden-
bosch and Ginzberg 1996). For example, McKin-
nsey’s Practice Development Network places core
project documentation online for the purposes of
promoti ng memory and learning organization-wide
(Stein and Zwass 1995). IT can play an important
role in the enhancement and expansion of both
semantic and episodic organizational memory.
Document management technology allows knowl-
edge of an organization’s past, often dispersed
among a variety of retention facilities, to be effec-
tively stored and made accessible (Stein and
Zwass 1995). Drawing on these technologies,
most consulting firms have created semantic
memories by developing vast repositories of
knowledge about customers, projects, compe-
tition, and the industries they serve (Alavi 1997).
Knowledge Transfer
Having discussed knowledge creation and
storage/retrieval, we now expand Figure 1 into
Figure 2 and consider the important issue of
knowledge transfer. The arrows from Figure 1 are
now represented as two-way arrows.
In Figure 2, the arrows labeled D represent the
process of knowledge application and those
labeled E represent the learning, or new knowl-
edge creation, that occurs when individuals apply
knowledge and observe the results. The arrows
labeled F represent the transfer of an individual’s
explicit knowledge to group semantic memory
(which can occur, for instance, when individuals
place reports they have prepared on a group
server for others to view). The arrows labeled G
represent the possible transfer from individual tacit
knowledge to group episodic memory. Individuals
may likewise learn from the group semantic and
episodic memories, reflected in arrows F and G.
Indeed, the group episodic memory is critical in
helping an individual interpret and learn from the
group semantic memory.
As the figure illustrates, an important process in
knowledge management is that of knowledge
transfer, with each transfer of knowledge repre-
sented by an arrow. Transfer occurs at various
levels: transfer of knowledge between individuals,
from individuals to explicit sources, from indivi-
duals to groups, between groups, across groups,
and from the group to the organization.
Considering the distributed nature of organi-
zational cognition, an important process of knowl-
edge management in organizational settings is the
transfer of knowledge to locations where it is
needed and can be used. However, this is not a
simple process in that organizations often do not
know what they know and have weak systems for
locating and retrieving knowledge that resides in
them (Huber 1991). Communication processes
and information flows drive knowledge transfer in
organizations. Gupta and Govindarajan (2000)
have conceptualized knowledge transfer (knowl-
edge flows in their terminology) in terms of five
Alavi & Leidner/Knowledge Management
120 MIS Quarterly Vol. 25 No. 1/March 2001
Individual A’s Individual B’s
Storage (documents,
email)
Tacit Knowledge Tacit Knowledge
Individual A’s
Explicit Knowledge Individual B’s
Explicit Knowledge
Storage (documents,
email)
Knowledge
Application
Knowledge
Application
Group 1’s Episodic
Memory
Group 1’s semantic memory
E
E
D
D
F
GG
Legend:
D--The Process of Knowledge Application
E--The Process of Learning
F--The Transfer of Individual Explicit Knowledge to Group Semantic Memory and vice versa
G--The Transfer of Individual Tacit Knowledge to Group Episodic Memory and vice versa
F
Individual A’s Individual B’s
Storage (documents,
email)
Tacit Knowledge Tacit Knowledge
Individual A’s
Explicit Knowledge Individual B’s
Explicit Knowledge
Storage (documents,
email)
Knowledge
Application
Knowledge
Application
Group 1’s Episodic
Memory
Group 1’s semantic memory
E
E
D
D
F
GG
Legend:
D--The Process of Knowledge Application
E--The Process of Learning
F--The Transfer of Individual Explicit Knowledge to Group Semantic Memory and vice versa
G--The Transfer of Individual Tacit Knowledge to Group Episodic Memory and vice versa
F
Figure 2. Knowledge Transfer among Individuals in a Group
elements: (1) perceived value of the source unit’s
knowledge, (2) motivational disposition of the
source (i.e., their willingness to share knowledge),
(3) existence and richness of transmission chan-
nels, (4) motivational disposition of the receiving
unit (i.e., their willingness to acquire knowledge
from the source), and (5) the absorptive capacity
of the receiving unit, defined as the ability not only
to acquire and assimilate but also to use knowl-
edge (Cohen and Levinthal 1990). The least con-
trollable element is the fifth: knowledge must go
through a recreation process in the mind of the
receiver (El Sawy et al. 1998). This recreation
depends on the recipient’s cognitive capacity to
process the incoming stimuli (Vance and Eynon
1998).
The majority of the literature focuses on the third
element, that of the knowledge transfer channels.
Knowledge transfer channels can be informal or
formal, personal or impersonal (Holtham and
Courtney 1998). Informal mechanisms, such as
unscheduled meetings, informal seminars, or
coffee break conversations, may be effective in
promoting socialization but may preclude wide
dissemination (Holtham and Courtney 1998).
Such mechanisms may also be more effective in
small organizations (Fahey and Prusak 1998).
However, such mechanisms may involve certain
amounts of knowledge atrophy in that, absent a
formal coding of the knowledge, there is no
guarantee that the knowledge will be passed
Alavi & Leidner/Knowledge Management
MIS Quarterly Vol. 25 No. 1/March 2001 121
accurately from one member to others. This
parallels problems with the recipient’s ability to
process the knowledge. Learning problems can
involve recipients filtering the knowledge they
exchange, interpreting the knowledge from their
own frame of reference, or learning from only a
select group of knowledge holders (Huysam et al.
1998). Formal transfer mechanisms, such as
training sessions and plant tours, may ensure
greater distribution of knowledge but may inhibit
creativity. Personal channels, such as appren-
ticeships or personnel transfers, may be more
effective for distributing highly context specific
knowledg e whereas impersonal channels, such as
knowledge repositories, may be most effective for
knowledge that can be readily generalized to other
contexts. Personnel transfer is a formal, personal
mechanism of knowledge transfer. Such trans-
fers, common in Japan, immerse team members
in the routines of other members, thereby allowing
access to the partner’s stock of tacit knowledge
(Fahey and Prusak 1998). A benefit is that
learning takes place without the need to first
convert tacit knowledge to explicit, saving time
and resources and preserving the original knowl-
edge base (Fahey and Prusak 1998). The most
effective transfer mechanism depends upon the
type of knowledge being transferred (Inkpen and
Dinur 1998). Much as the existence of “care” may
be important to knowledge transfer between
individuals, the existence of a close, tight interface
is critical at the organizational level. A narrow and
distant interface has been found to be an obstacle
to learning and knowledge sharing (Inkpen and
Dikur 1998).
IT can support all four forms of knowledge
transfer, but has mostly been applied to informal,
impersonal means (through such venues as Lotus
Notes discussion databases) and formal, imper-
sonal means (such as knowledge maps or corpor-
ate directories). An innovative use of technology
for transfer is the use of intelligent agent software
to develop interest profiles of organizational mem-
bers in order to determine which members might
be interested recipients of point-to-point electronic
messages exchanged among other members
(O’Dell and Grayson 1998). Employing video
technologies can also enhance transfer. For
example, offshore drilling knowledge is made
available globally at British Petroleum by desktop
video conferencing in which a screen will include
images of the participants, windows of technical
data, video clips of the physical issue under consi-
deration, specifications, contractual data, and
plans (Cranfield University 1998).
IT can increase knowledge transfer by extending
the individual’s reach beyond the formal communi-
cation lines. The search for knowledge sources is
usually limited to immediate coworkers in regular
and routine contact with the individual. However,
individuals are unlikely to encounter new knowl-
edge through their close-knit work networks
because individuals in the same clique tend to
possess similar information (Robertson et al.
1996). Moreover, studies show that individuals
are decidedly unaware of what their cohorts are
doing (Kogut and Zander 1996). Thus, expanding
the individual’s network to more extended,
although perhaps weaker, connections is central
to the knowledge diffusion process because such
networks expose individuals to more new ideas
(Robertson et al. 1996). Computer networks and
electronic bulletin boards and discussion groups
create a forum that facilitates contact between the
person seeking knowledge and those who may
have access to the knowledge. For example, this
may be accomplished by posting a question in the
form of “does anybody know” or a “request for
help” to the discussion group. Corporate direc-
tories may enable individuals to rapidly locate the
individual who has the knowledge that might help
them solve a current problem. At Hewlett-
Packard, the primary content of one system is a
set of expert profiles containing a directory of the
backgrounds, skills, and expertise of individuals
who are knowledgeable on various topics. Often
such metadata (knowledge about where the
knowledge resides) proves to be as important as
the original knowledge itself (Andreu and Ciborra
1997). Providing taxonomies or organizational
knowledge maps enables individuals to rapidly
locate either the knowledge or the individual who
has the needed knowledge, more rapidly than
would be possible without such IT-based support
(Offsey 1997).
Alavi & Leidner/Knowledge Management
122 MIS Quarterly Vol. 25 No. 1/March 2001
Knowledge Application
An important aspect of the knowledge-based
theory of the firm is that the source of competitive
advantage resides in the application of the
knowledge rather than in the knowledge itself.
Grant (1996b) identifies three primary mechan-
isms for the integration of knowledge to create
organizational capability: directives, organizational
routine s, and self-con tained task teams. Directives
refer to the specific set of rules, standards, pro-
cedures, and instructions developed through the
conversion of specialists’ tacit knowledge to expli-
cit and integrated kn owledge for efficient c ommun-
ication to non-specialists (Demsetz 1991).
Examples include directives for hazardous waste
disposal or airplane safety checks and main-
tenance. Organizational routines refer to the
development of task performance and coordi-
nation patterns, interaction protocols, and process
specifications that allow individuals to apply and
integrate their specialized knowledge without the
need to articulate and communicate what they
know to others. Routines may be relatively simple
(e.g., organizing activities based on time-
patterned sequences such as an assembly line),
or highly complex (e.g., a cockpit crew flying a
large passenger airplane). The third knowledge
integration mechanism is the creation of self-
contained task teams. In situations in which task
uncertainty and complexity prevent the speci-
fication of directives and organizational routines,
teams of individuals with prerequisite knowledge
and specialty are formed for problem solving.
Technology can support knowledge application by
embedding knowledge into organizational rou-
tines. Procedures that are culture-bound can be
embedded into IT so that the systems themselves
become examples of organizational norms. An
example is Mrs. Field’s use of systems designed
to assist in every decision from hiring personnel to
when to put free samples of cookies out on the
table. The system transmits the norms and beliefs
held by the head of the company to organizational
members (Bloodgood and Salisbury 1998). Tech-
nology enforced knowledge application raises a
concern that knowledge will continue to be applied
after its real usefulness has declined. W hile the
institutionalization of “best practices” by em-
bedding them into IT might facilitate efficient
handling of routine, “linear,” and predictable situa-
tions during stable or incrementally changing
environments, when change is radical and dis-
continuous, there is a persistent need for con-
tinual renewal of the basic premises underlying
the practices archived in the knowledge reposi-
tories (Malhotra 1999). This underscores the need
for organizational members to remain attuned to
contextual factors and explicitly consider the
specific circumstances of the current environ-
ment. A second problem may be deciding upon
the rules and routines to apply to a problem, given
that over time, the organization has learned and
codified a large number of rules and routines, so
that choosing which rules to activate for a specific
choice making scenario is itself problematic.
Shared meanings and understandings about the
nature and needs of a particular situation can be
used to guide rule activation (Nolan Norton 1998).
Although there are challenges with applying
existing knowledge, IT can have a positive
influence on knowledge application. IT can
enhance knowledge integration and application by
facilitating the capture, updating, and accessibility
of organizational directives. For example, many
organizations are enhancing the ease of access
and maintenance of their directives (repair
manuals, policies, and standards) by making them
available on corporate intranets. This increases
the speed at which changes can be applied. Also,
organizational units can follow a faster learning
curve by accessing the knowledge of other units
having gone through similar experiences. More-
over, by increasing the size of individuals’ internal
social networks and by increasing the amount of
organiza tional memory available, information tech-
nologies allow for organizational knowledge to be
applied across time and space. IT can also
enhance the speed of knowledge integration and
application by codifying and automating organi-
zational routines. Workflow automation systems
are examples of IT applications that reduce the
need for communication and coordination and
enable more efficient use of organizational
routines through timely and automatic routing of
work-related documents, information, rules, and
activities. Rule based expert systems are another
means of capturing and enforcing well specified
organizational procedures.
Alavi & Leidner/Knowledge Management
MIS Quarterly Vol. 25 No. 1/March 2001 123
Individual A’s Individual B’s
Storage (documents,
email)
Tacit Knowledge Tacit Knowledge
Individual A’s
Explic it Knowledg e
Individual B’s
Explicit Knowledge
Storage (documents,
email)
Knowledge
Application
Knowledge
Application
Group 1’s semantic memory
Group 2’s semantic memory Group 3’s semantic memory
Knowledge
Application
Knowledge
Application
Individual C’s
Tacit Knowledge
Group 2’s Episodic
Memory
Group 1’s Episodic
Memory
Group 3’s Episodic
Memory
Individual D’s
Tacit Knowledge
Individual C’s
Explicit Knowledge
Individual D’s
Explicit Knowledge
H
J
H
H H
JJ
II
II
Legend:
H--An individual drawing upon gro up memory and applying the knowledge to a situation.
I-- The learning derived from an individua l in applying knowledge that becomes part of the group’s episod ic memory.
J--The sharing of knowledge across group s ystems, such as the sharing of best practices.
Individual A’s Individual B’s
Storage (documents,
email)
Tacit Knowledge Tacit Knowledge
Individual A’s
Explic it Knowledg e
Individual B’s
Explicit Knowledge
Storage (documents,
email)
Knowledge
Application
Knowledge
Application
Group 1’s semantic memory
Group 2’s semantic memory Group 3’s semantic memory
Knowledge
Application
Knowledge
Application
Individual C’s
Tacit Knowledge
Group 2’s Episodic
Memory
Group 1’s Episodic
Memory
Group 3’s Episodic
Memory
Individual D’s
Tacit Knowledge
Individual C’s
Explicit Knowledge
Individual D’s
Explicit Knowledge
H
J
H
H H
JJ
II
II
Legend:
H--An individual drawing upon gro up memory and applying the knowledge to a situation.
I-- The learning derived from an individua l in applying knowledge that becomes part of the group’s episod ic memory.
J--The sharing of knowledge across group s ystems, such as the sharing of best practices.
Legend:
H--An individual drawing upon gro up memory and applying the knowledge to a situation.
I-- The learning derived from an individua l in applying knowledge that becomes part of the group’s episod ic memory.
J--The sharing of knowledge across group s ystems, such as the sharing of best practices.
Figure 2. Knowledge Transfer among Individuals in a Group
Summary: Organizational Knowledge
Management Processes
To summarize, this section has described and
elaborated on a knowledge management frame-
work based on the view of organizations as
knowledge systems. One of the important impli-
cations of this framework is that knowledge
management consists of a dynamic and con-
tinuous set of processes and practices embedded
in individuals, as well as in groups and physical
structures. At any point in time and in any part of
a given organization, individuals and groups may
be engaged in several different aspects and
processes of knowledge management. Thus,
knowledge management is not a discrete, inde-
pendent, and monolithic organizational pheno-
menon. Figure 3 builds upon Figure 2 to illustrate
the “web” of knowledge management activities in
organizational settings. The figure introduces two
new groups—Groups 2 and 3—to illustrate the
potential knowledge transfer across groups. For
simplicity purposes, only one member is repre-
sented in Groups 2 and 3.
Figure 3 depicts the transfer of knowledge among
individuals and groups. Once individual A shares
(transfers) some knowledge with individual B,
individual B’s knowledge processes may have
been triggered. For example, A’s knowledge
transfer may lead to B’s knowledge creation. B
may chose to apply the knowledge, consult with
other members, or record the knowledge.
Knowledge hence flows between individuals and
Alavi & Leidner/Knowledge Management
124 MIS Quarterly Vol. 25 No. 1/March 2001
a major challenge of KM is to facilitate these flows
so that the maximum amount of transfer occurs
(assuming that the knowledge individuals create
has value and can improve performance).
Individuals in a group or community of practice
then develop a group knowledge (the collectivity
of their stored memory, be it organized informally
in e-mail communications or formally in a
knowledge repository). The individual is con-
nected to the group processes through transfer
(an individual may share knowledge with the
group during a decision-making meeting, for
example) or through a centralized storage
mechanism (e.g., computer files or regular
meetings). Individuals can then call on the
centralized memory to make decisions, if needed
(arrows H). Individuals learn from the application
of knowledge and their learning becomes
embedded into their tacit knowledge space and
the group’s episodic memory (arrows I). Organi-
zational knowledge processes would then consist
of the summation of the individual and group
knowledge processes. In this case, one group
may have acquired and applied knowledge to a
given situation and coded this knowledge in the
form of a certain routine. This “best practice” may
then be shared with other groups by allowing
access to group memory systems (arrows J) or by
facilitating intergroup dialogue.
Figure 3 can elucidate some of the major chal-
lenges of knowledge management at the indivi-
dual, group, and the organizational (i.e., inter-
groups) levels. One primary challenge is to make
individual knowled ge available, and meaningful, to
others (Ackerman and Halverson 1999). At the
group level, this means enabling a group’s
episodic memory to be accessible to other groups,
implying an overlap in group membership. The
codification of knowledge into semantic memory
neither guarantees efficient dissemination nor
effective storage (Jordan and Jones 1997).
Transfer among groups may be challenged not
only by the lack of shared episodic memory, but
by the practical issue of informing groups of when
the semantic memory of a group has been modi-
fied (say, a new important document summarizing
a flaw in product design is now available on the
group intranet of an overseas R&D unit). Even if
one group is aware of, and chooses to access,
another’s semantic memory, how does the
receiving group validate the information and
determine whether to apply it? Group gate-
keepers (internal boundary spanners) may act as
links between the episodic memory of two groups
and, hence, increase the relevance of knowledge
transfer. Do certain individuals act as such inter-
nal boundary spanners, searching within an
extended network for practices that might improve
their unit? In short, to improve knowledge man-
agement, utilizing information technology implies
attention not only to improving the individual and
group level processes of knowledge creation and
storage, but also to improving the linkages among
individuals and between groups.
Another implication of this framework is that the
four knowledge processes of creation, storage/
retrieval, transfer, and application are essential to
effective organizational knowledge management.
We contend that the application of information
technologies can create an infrastructure and
environment that contribute to organizational
knowledge management by actualizing, sup-
porting, augmenting, and reinforcing knowledge
processes at a deep level through enhancing their
underlying dynamics, scope, timing, and overall
synergy. Table 3 summarizes the four processes
and the potential role of IT in facilitating each
process. While the four processes are presented
as discrete, it is important to realize that we are
not implying a linear sequence, as evident in the
Figures 1, 2 and 3. An individual may create new
knowledge (have a new insight) and immediately
apply this knowledge (use it as the basis of a
decision, for example) without either storing it
(except in his/her internal memory) or transferring
it to others. The application of the knowledge may
lead to additional new knowledge (perhaps
concerning how best to apply the knowledge),
which may or may not be coded or transferred.
Knowledge that has been applied might be coded
after application (e.g., incorporated into an organi-
zational routine). The objective of Table 3 is not to
provide an exhaustive set of IT tools for KM, but to
illustrate that a variety of IT tools may be drawn
upon for support of different KM processes in
organizations.
Table 3. Knowledge Management Processes and the Potential Role of IT
Knowledge
Management
Processes
Knowledge
Creation
Knowledge
Storage/Retrieval
Knowledge
Transfer
Knowledge
Application
Supporting
Information
Technologies
Data mining
Learning tools
Electronic bulletin boards
Knowledge repositories
Databases
Electronic bulletin boards
Discussion forums
Knowledge directories
Expert systems
Workflow systems
IT Enables Combining new sources of
knowledge
Just in time learning
Support of individual and
organizational memory
Inter-group knowledge
access
More extensive internal
network
More communication
channels available
Faster access to
knowledge sources
Knowledge can be applied
in many locations
More rapid application of
new knowledge through
workflow automation
Platform
Technologies
Groupware and communication technologies
INTRANETS
Alavi & Leidner/Knowledge Management
126 MIS Quarterly Vol. 25 No. 1/March 2001
Research Issues in Knowledge
Management
The review of the literature on knowledge, knowl-
edge management, and knowledge management
systems uncovers a broad gamut of potential
research streams. While much theory exists on
knowledge management, little empirical work has
been undertaken. Hence, there are large gaps in
the body of knowledge in this area. In this sec-
tion, we will briefly highlight some research
themes that, in our view, aim at bridging the gaps.
Research Issues on
Knowledge Creation
Much of the existing research on knowledge
creation focuses on the source and state of knowl-
edge. Research is now needed that moves
beyond the source and state to consider the con-
ditions that facilitate knowledge creation. Descrip-
tive studies have identified culture as a major
catalyst, or alternatively a major hindrance, to
knowledge creation and sharing. A knowledge-
friendly organizational culture has been identified
as one of the most important conditions leading to
the success of KM initiatives in organizations
(Davenport and Prusak 1998). Firm-wide KMS
usually require profound cultural renovations be-
cause, traditionally, organizations have rewarded
their professionals and employees based on their
individual performance and know-how. Cultural
barriers to KM (e.g., organizational norms that pro-
mote and encourage knowledge hoarding) cannot
be effectively reduced or eliminated through IT
applications. In many organizations, a major cul-
tural shift may be required to change employees’
attitudes and behavior so that they willingly and
consistently share their knowledge and insights.
If so, must cultural change occur before knowl-
edge management initiatives can be successfully
undertaken or can knowledge management initia-
tives facilitate cultural change? What cultures
foster knowledge creation? Research can exa-
mine the relationships between various organi-
zational cultures and knowledge creation.
Organizational design, in particular the building of
communities of practice and shared knowledge
creation spaces, is also considered an important
catalyst for knowledge creation. For instance, at
3M, employees can set aside 15% of their work
time to pursue personal research interests.
Computer terminals are located throughout the
company, including large open meeting areas
around which people may gather to partake in
discussions. In concert with the integration of
open access to knowledge databases, coor-
dination between production, marketing, distri-
bution, and product design is improved (Graham
and Pizzo 1998). As was shown in Figure 3,
individuals may benefit more from semantic
memory if they also share an episodic memory.
Organizational design can be used to increase the
episodic memory and, hence, make the semantic
memory more readily interpretable.
Some argue that the close ties in a community
limit knowledge creation because individuals are
unlikely to encounter new ideas in close-knit
networks where they tend to possess similar
information (Robertson et al. 1996). This view
upholds the need for weak ties to expose indivi-
duals to new ideas that can trigger new knowledge
creation. In terms of design, much can be done to
encourage knowledge creation, storage/retrieval,
and transfer. Distant, informal, spontaneous con-
tact between different organizational subunits
might be an important mechanism for knowledge
creation (Roberston et al. 1996). The alternate
view argues that knowledge creation is better
served by close ties in a community of practice
since individuals share a common language and
would be more at ease discussing ideas openly
and challenging the ideas of others. Moreover,
such communities develop a shared under-
standing or a “collective knowledge base” (Brown
and Duguid 1998) from which knowledge
emerges. Hayduk (1998) hypothesizes that
learning processes are more effective when
shared within or among a self-selected peer
group. Thus, one research question whether IT
can enhance knowledge creation by enabling
weak ties (e.g., spontaneous e-mail exchanges
among distant members of an organization) while
reinforcing close ties (by allowing more frequent
interactions among the members of a community
of practice). Can, and if so, how do, communities
of practice evolve rapidly through electronic
connections and interactions alone?
Alavi & Leidner/Knowledge Management
MIS Quarterly Vol. 25 No. 1/March 2001 127
Table 4. Research Questions Concerning Knowledge Creation
Research Question 1: What conditions facilitate knowledge creation in organizations?
Research Question 1a: Do certain organizational cultures foster knowledge creation?
Research Question 1b: Can IT enhance knowledge creation by enabling weak ties to develop and
by reinforcing existing close ties?
Research Question 1c: How is knowledge originating from outside a unit evaluated for internal use?
Research Question 1d: Does lack of a shared context inhibit the adoption of knowledge originating
from outside a unit?
Research is also needed to determine how tight
collaboration should be within the shared space to
improve and accelerate knowledge creation and
whether shared knowledge creation spaces can
be designed in such a manner to tighten collabor-
ation (El Sawy et al. 1998). Research could also
consider how knowledge coming from outside the
shared space is evaluated: does a lack of context
prevent the effective adoption of outside knowl-
edge? Or are members able to adopt and modify
outside knowledge to meet their needs? Answers
to these questions have implications for the appro-
priate scale and features of knowledge manage-
ment systems. Table 4 summarizes the research
questions concerning knowledge creation.
Research Issues on Knowledge
Storage and Retrieval
Knowledge storage involves obtaining the knowl-
edge from organizational members and/or exter-
nal sources, coding and indexing the knowledge
(for later retrieval), and capturing it. Incentives are
important to overcome some of the major barriers
to knowledge storage success. These barriers
include the lack of employee time to contribute
their knowledge (Cranfield University 1998; KPMG
1998b) and a corporate culture that has histori-
cally not rewarded contributing and sharing of
insights (Brown and Duguid 1998; Cranfield Uni-
versity 1998; KPMG 1998b). Many organizations
are relatively lean and many employees do not
have time to make knowledge available, share it
with others, teach and mentor others, use their
expertise to innovate, or find ways of working
smarter (Glazer 1998). Instead, they are task-
focused, shifting existing workloads to fight dead-
lines. Moreover, in many organizations, members
feel that their futures with the company are
dependent upon the expertise they generate and
not on the extent to which they help others. In
such situations, it is then expected that individuals
will attempt to build up and defend their own
hegemonies of knowledge (von Krogh 1998).
People may be unaware of what they have
learned; moreover, even if they realize what they
have learned from a project, they may be unaware
of what aspects of their learning would be relevant
for others. Without a systematic routine for cap-
turing knowledge, a firm might not benefit from its
best knowledge being captured. Research is
needed to address the issue of what types of
incentives are effective in inculcating organiza-
tional members with valuable knowledge to
contribute and share their knowledge.
An important consideration with storing knowledge
is how much context to include. When the context
surrounding knowledge creation is not shared, it is
questionable whether storing the knowledge
without sufficient contextual detail will result in
effective uses. This could lead to the essence of
the knowledge being lost (Zack 1998c). In addi-
tion to the question of how much context to
capture is the question of how much knowledge to
code and store. The more readily available the
knowledge, the more likely its reuse. On the other
hand, the more readily available, the greater the
likelihood of knowledge misuse, i.e., knowledge
being misapplied to a different context. Further-
more, today’s knowledge may be tomorrow’s
ignorance in the sense that knowledge emerges
Alavi & Leidner/Knowledge Management
128 MIS Quarterly Vol. 25 No. 1/March 2001
Table 5. Research Questions Concerning Knowledge Storage and Retrieval
Research Question 2: What incentives are effective in encouraging knowledge contribution and
sharing in organizations?
Research Question 2a: How much context needs to be included in knowledge storing to ensure
effective interpretation and application?
Research Question 2b: Is stored knowledge accessed and applied by individuals who do not know
the originator of the knowledge?
Research Question 2c: What retrieval mechanisms are most effective in enabling knowledge
retrieval.
and evolves over time and any system designed
to store the knowledge must ensure that the
knowledge is dynamic and updated rather than
static. To be useful, it should be easy to retrieve
the captured knowledge. Creation of easy to use
and easy to remember retrieval mechanisms (e.g.,
search and retrieval commands) are important
aspects of an organizational KM strategy. A
variety of search and retrieval approaches and
tools (e.g., browsers) to access organizational
knowledge captured in data warehouses and
knowledge repositories exist. Two general models
to information retrieval exist, the “pull” and the
“push” models. The pull model is the traditional
model and involves search for and retrieval of
information based on specific user queries. In the
push model, information is automatically retrieved
and delivered to the potential user based upon
some predetermined criteria. The challenge in
design of organizational knowledge retrieval stra-
tegies is providing timely and easy access to
knowledge while avoiding a condition of informa-
tion overload. Thus, as summarized in Table 5,
research is needed to address several important
issues regarding knowledge storage and retrieval.
Research Issues on
Knowledge Transfer
The notion of knowledge transfer raises several
important issues: first is the question of to what
degree knowledge needs to be, and even can be,
transferred internally, which may depend upon the
extent of interdependency among subgroups or
individuals (Leonard and Sensiper 1998). Given
the ease with which individuals are able to transfer
the explicit components of their knowledge, we
would expect them to transfer more knowledge
than they would if they had to rely solely on verbal
or face-to-face communication. However, this
does not imply that individuals will expand the
number of other people with whom they share
knowledge. They may simply share more with the
same individuals (such as via e-mail or group-
ware) by virtue of the ease and speed with which
they are able to electronically transfer information
to their cohorts. Thus, a primary question con-
cerning knowledge transfer is the degree to which
knowledge transfer is increased in an organization
as a result of applying information technology to
the knowledge management initiative.
A second major issue involves locating knowl-
edge, both how to find needed knowledge
documents and how to find the knowledge needed
within a large collection of documents (Dworman
1998). One system, Homer, sorts through col-
lections of documents to find specific information
relevant to a query as well as to identify patterns
of information in a large collection of documents
(Dworman 1998). A problem, similar to the infor-
mation overload problem, exists when individuals
are aware that the relevant knowledge exists in
organizational memory, but are discouraged from
searching for the knowledge by the sheer volume
of available knowledge. For example, most devel-
opers at Hewlett-Packard are aware that the
SPaM system holds all of their past projects
history, but rarely seek answers in SPaM because
finding the answer would take days (Powell 1998).
Thus, research on the development of effective
organizational and technical strategies for orga-
nizing, retrieving, and transmitting knowledge are
needed to facilitate knowledge transfer.
Alavi & Leidner/Knowledge Management
MIS Quarterly Vol. 25 No. 1/March 2001 129
Table 6. Research Questions Concerning Knowledge Transfer
Research Question 3: How can knowledge be effectively transferred among organizational units?
Research Question 3a: To what degree does the application of IT to knowledge transfer increase
the transfer of knowledge among individuals within a group and between groups?
Research Question 3b: What organizational and technical strategies are effective in facilitating
knowledge transfer?
Research Question 3c: What social, cultural, or technical attributes of organizational settings
encourage knowledge transfer by balancing the push and pull processes?
Research Question 3d: Does the application of IT to knowledge transfer inadvertently discourage
external searches for knowledge?
A third important issue on knowledge transfer
concerns knowledge flows between the provider
(source) and the knowledge seeker. From the
provider’s perspective, flow is a selective pull pro-
cess; from a seeker’s perspective, flow is a selec-
tive push process (Holthouse 1998). Balancing
the pull and push processes then is an important
aspect of knowledge transfer in organizations.
Research that focuses on social, cultural, and
technical attributes of organizational settings that
encourage and facilitate knowledge flows by
balancing the push and pull processes is
important.
Finally, a consideration with knowledge transfer is
the extent to which individuals discontinue exter-
nal searches for new knowledge and rely solely on
internal knowledge, so that knowledge is trans-
ferred internally but little external knowledge is
transferred into the organization. A reliance on IT
may facilitate the process of coding knowledge
into semantic memory and improving internal link-
ages within a group and among groups, but
individuals may consequently spend more time
focusing on internal than external searches for
knowledge. Table 6 summarizes the research
questions concerning knowledge transfer.
Research Issues on
Knowledge Application
The processes of knowledge creation, storage/
retrieval, and transfer do not necessarily lead to
enhanced organizational performance; effective
knowledge application does. Organizational per-
formance often depends more on an ability to turn
knowledge into effective action and less on
knowledge itself. It is widely recognized that orga-
nizations have gaps between what they know and
what they do (Pfeffer and Sutton 2000). There
may be several reasons for organizational mem-
bers to access and assimilate knowledge but not
apply it (i.e., act upon it). Reasons include dis-
trusting the source of knowledge, lack of time or
opportunity to apply knowledge, or risk aversion
(particularly in organizations that punish mistakes)
(Davenport and Prusak 1998). Thus, knowledge
access and transfer are only partial steps toward
knowledge application. Learning literature pro-
vides us with some important insights into the
cognitive processes underlying knowledge
absorption and its applications to problem solving
and decision making by individuals. For example,
work in the area of knowledge structures has
demonstrated that in most cases the cognitive
processes (problem solving and decision making)
of individuals in organizational settings are
enacted with little attention and through invoking
preexisting knowledge and cognitive “routines”
(Gioia and Pool 1984). This approach leads to
reduction in cognitive load and is, therefore, an
effective strategy in dealing with individual cogni-
tive limitations. On the other hand, it creates a
barrier to search, absorption, and application of
new knowledge in organizations (Alavi 2000).
An important area of KM research consists of an
identification of these factors and the development
of organizational practices and systems to bridge
the knowledge application gap. Table 7 sum-
marizes the research questions concerning knowl-
edge application.
Alavi & Leidner/Knowledge Management
130 MIS Quarterly Vol. 25 No. 1/March 2001
Table 7. Research Questions Concerning Knowledge Application
Research Question 4: How can an organization encourage application of knowledge that is made
available?
Research Question 4a: What factors contribute to the knowing-doing gap in organizations and how
can they be reduced or eliminated?
Research Question 4b: What organizational practices can help bridge the knowledge application
gap?
IT and the Knowledge
Management Initiatives
The above four areas of research questions
included questions related to the role of IT in the
four knowledge management processes. There
are also many broad questions related to the role
and impact of IT on knowledge management
initiatives, several of which are highlighted in this
section.
Our analysis of the literature suggests that IT can
lead to a greater breadth and depth of knowledge
creatio n, storage, transfer, and application in orga-
nizations. While these suppositions in general
can be applied to most IT designed to provide
information and could form the subject of research
in themselves, an interesting line of research
would consider the subsequent question of
whether and how having knowledge available from
more vertical and horizontal sources in the orga-
nization in a more timely manner may enhance
individual and organizational performance. Does
an increase in the breadth and depth of knowl-
edge result in greater use of a knowledge
management system and greater use of available
knowledge, or contrarily, does such an expanded
availability discourage usage as the potential
search and absorption time for needed knowledge
might simultaneously increase? Does an increase
in the breadth, depth, quality, and timeliness of
organizational knowledge result in improved deci-
sion making, reduced product cycles, greater
productivity, or better customer service? In
general, what are the consequences of increasing
the breadth, depth, quality, and timeliness of
organizational knowledge?
There is debate as to whether information tech-
nology inhibits or facilitates knowledge creation
and use. On the one hand, some argue that cap-
turing knowledge in a KMS inhibits learning (Cole
1998) and may result in the same knowledge
being applied to different situations even when it
might not be appropriate. Proponents of this view
maintain that IT plays a limited role in knowledge
creation because IT is only helpful if an individual
knows what he is looking for (the search is
necessary but the solution is obvious) (Powell
1998). In this case, little new knowledge creation
can occur. Moreover, some argue that the mech-
anistic and rigid nature of IT-based KM is
incapable of keeping pace with dynamic needs of
knowledge creation (Malhotra 1999). However,
this argument is not so much about information
technology as about the role of explicit knowledge.
The issue is how to ensure that individuals modify
explicit knowledge to meet their situation and
thereby create new knowledge. Once individuals
modify and use knowledge from a KMS, do they
then transfer their experiences into modified
knowledge for others to use, or is existing knowl-
edge continually reused in various ways with no
record of the modifications? What level of trust do
individuals have in knowledge that resides in a
system but the originator of which they do not
personally know? How can trust be developed to
enhance the individual’s use of knowledge in a
KMS?
As with most information systems, the success of
KMS partially depends upon the extent of use,
which itself may be tied to system quality, infor-
mation quality, and usefulness (Delone and
McLean 1992). System quality is influenced by
attributes such as ease of use, characteristics of
human-computer interface, and flexibility and
effectiveness of search mechanisms. Research
focusing on KMS use process, and development
of intuitive search, retrieval, and display, is
Alavi & Leidner/Knowledge Management
MIS Quarterly Vol. 25 No. 1/March 2001 131
Table 8. Research Questions Concerning the Application of IT to Knowledge
Management
Research Question 5: What are the consequences of increasing the breadth and depth of available
knowledge, via information technology, on organizational performance?
Research Question 5a: How can an organization ensure that knowledge captured via information
technology is effectively modified where necessary prior to application?
Research Question 5b: How can an organization ensure that IT captures modifications to
knowledge along with the original knowledge?
Research Question 5c: How do individuals develop trust in knowledge captured via IT, the
originator of which they may not know?
Research Question 5d: What factors are related to the quality and usefulness of information
systems applied to knowledge management initiatives?
needed to enhance KMS quality. At the level of
knowledge quality, issues pertain to what kinds of
knowledge can be usefully codified and at what
level of detail, how to protect coded knowledge
from unauthorized access or copying, and how to
ensure that the knowledge is maintained (KPMG
1998b). In terms of KMS usefulness, studies can
examine the extent to which available knowledge
is reused. Ratios of knowledge accessed to
knowledge available and knowledge used to
knowledge accessed could give an indication of
system usefulness. Equally important to consider
would be the number of searches yielding no use-
ful knowledge. Table 8 summarizes the research
questions concerning the application of IT to
knowledge management initiatives.
Summary and Conclusions
In this paper, we have presented a discussion of
knowledge, knowledge management, and knowl-
edge management systems based on a review,
interpretation, and synthesis of a broad range of
relevant literature. Several general conclusions
may be drawn from our work.
1. The literature review revealed the complexity
and multi-faceted nature of organizational
knowledge and knowledge management. Dif-
ferent perspectives and taxonomies of knowl-
edge were reviewed and discussed. For
example, knowledge may be tacit or explicit;
it can refer to an object, a cognitive state, or
a capability; it may reside in individuals,
groups (i.e., social systems), documents, pro-
cesses, policies, physical settings, or com-
puter repositories. Thus, no single or opti-
mum approach to organizational knowledge
management and knowledge management
systems can be developed. A variety of
knowledge management approaches and
systems needs to be employed in organiza-
tions to effectively deal with the diversity of
knowledge types and attributes.
2. Knowledge management involves distinct but
interdependent processe s of knowledge c rea-
tion, knowledge storage and retrieval, knowl-
edge transfer, and knowledge application. At
any point in time, an organization and its
members can be involved in multiple knowl-
edge management process chains. As such,
knowledge management is not a monolithic
but a dynamic and continuous organizational
phenomenon. Furthermore, the complexity,
resource requirements, and underlying tools
and approaches of knowledge management
processes vary based on the type, scope,
and characteristics of knowledge manage-
ment processes.
3. KMS, by drawing on various IT tools and
capabilities, can play a variety of roles in
support of organizational knowledge manage-
Alavi & Leidner/Knowledge Management
132 MIS Quarterly Vol. 25 No. 1/March 2001
ment processes. Specific examples of IT for
support of the four knowledge management
processes delineated in the paper were
presented in the framework section. It is
important to note that KMS, by drawing on
various and flexible IT capabilities, can lead
to various forms of KM support, extending
beyond the traditional storage and retrieval of
coded knowledge.
4. Research questions regarding organizational
knowledge management processes and the
role of IT in these processes were presented.
These questions could form the basis of
future research.
Organizational knowledge and knowledge man-
agement are popular topics in several extant
literatures including strategic management and
organizational theory as well as information
systems. It is thus important that IS researchers
be aware of, understand, and build upon the
already significant work in the large extant litera-
tures. This will provide the diversity of perspec-
tives and approaches that the study of such multi-
faceted and complex phenomenon requires.
It is our contention that in large global firms in
hypercompetitive environments, information tech-
nology will be interlaced with organizational knowl-
edge management strategies and processes. This
is based on the observation that, in these firms,
KM processes span time and geographic dis-
tance. This, combined with the need for very short
cycle times for product/service development and
innovation, necessitates reliance on information
and communication technologies. We, therefore,
believe that the role of IT in organizational knowl-
edge management ought to receive considerable
scholarly attention and become a focal point of
inquiry. It is our hope that the ideas, discussion,
and research issues set forth in this paper will
stimulate interest and future work in the knowl-
edge management area by IS researchers.
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About the Authors
Maryam Alavi is the John and Lucy Cook Chair of
Information Strategy, Goizueta Business School,
Emory University. Maryam’s publications have
appeared in several academic journals, including
Academy of Management Journal, Education
Technology Research and Development, Infor-
mation Systems Research, Management Science,
and MIS Quarterly. Maryam is the twice-elected
Vice President of Education of Association of
Information Systems (AIS). She was awarded the
Marvin Bower Faculty Fellowship at Harvard
Business School (1996-1997) and served as the
program co-chair of the 1990 ICIS (International
Conference on Information Systems), and the co-
chair of the 1995 ICIS Doctoral Consortium.
Maryam was elected as an AIS Fellow in 2000.
Dorothy E. Leidner is an associate professor of
information systems at Texas Christian University
in Fort Worth, Texas. She is on leave of absence
from INSEAD in Fontainebleau, France. Dorothy
received her Ph.D. in Information Systems from
the University of Texas at Austin, where she also
obtained her MBA and BA. She has previously
been on the faculty at Baylor University and has
been a visiting professor at the Instituto Tecno-
logico y des Estudios Superiores de Monterrey,
Mexico, at the Institut d’Administration des Entre-
prises at the Université de Caen, France, and at
Southern Methodist University in Dallas, Texas.
Dorothy has published her research in many
journals, including MIS Quarterly, Information
Systems Research, Organization Science, and the
Journal of Management Information Systems.
