organizational memory information systems: a transactive memory approach

www.elsevier.com/locate/dsw

Decision Support Systems 39 (2005) 549–562

Organizational memory information systems: a transactive

memory approach

Dorit Nevoa,*, Yair Wandb

aS337H, Schulich School of Business, York University, 4700 Keele St., Toronto, ON, Canada M3J1P3bSauder School of Business, University of British Columbia, Vancouver, BC, Canada

Available online 10 May 2004

Abstract

Effective management of organizational memory (OM) is critical to collaboration and knowledge sharing in organizations.

We present a framework for managing organizational memory based on transactive memory, a mechanism of collective memory

in small groups. While being effective in small groups, there are difficulties hindering the extension of transactive memory to

larger groups. We claim that information technology can be used to help overcome these difficulties. We present a formal

architecture for directories of meta-memories required in extended transactive memory systems and propose the use of meta-

knowledge to substitute for the lack of tacit group knowledge that exists in small groups.

D 2004 Elsevier B.V. All rights reserved.

Keywords: Organizational memory information system; Transactive memory; Meta-knowledge

1. Introduction the way organizations store knowledge from the past to

Organizational memory (OM) and knowledge man-

agement are two intertwined topics that have grown in

importance for businesses and academics over the past

few years. Knowledge management encompasses var-

ious practices of managing organizational knowledge

such as knowledge generation, capture, sharing, and

application [2]. Within these practices, effective shar-

ing and use of organizational knowledge depends—to

a large extent—on the organization’s ability to create

and manage its collective memory. This collective

memory is often referred to as organizational memory

(OM). The organizational memory can be described as

0167-9236/$ - see front matter D 2004 Elsevier B.V. All rights reserved.

doi:10.1016/j.dss.2004.03.002

* Corresponding author.

E-mail address: [email protected] (D. Nevo).

support present activities [24].

Organizational memory can increase organizational

effectiveness by supporting the coordination of work,

management of information, the organization’s re-

sponsiveness to changes, and the definition and pur-

suit of organizational goals [25]. Such memory

generally resides in different retainers in the organi-

zation and organization members retrieve its content

based on their work needs [28]. To support effective

management of organizational memory, Stein and

Zwass [25] propose the use of information technology

to accomplish four specific processes related to orga-

nizational memory: acquisition, retention, mainte-

nance, and search and retrieval. In addition, they

outline a design for an organizational memory infor-

mation system (OMIS) that includes a ‘‘mnemonic

D. Nevo, Y. Wand / Decision Support Systems 39 (2005) 549–562550

functions layer’’ intended to provide the functionality

necessary to support the above four processes. The

general design requirements of this layer include the

ability to capture and represent knowledge in OM, the

ability to communicate knowledge, and the mainte-

nance of the contents of the OM.

While the management of OM is a good candidate

for the use of information technology, the specific

design of such an information system is not a simple

task. We suggest there are five reasons for this.

First, much of the knowledge in the OM is contex-

tualized. When knowledge is transferred, the receiving

end of the communication system often does not know

the original context of the knowledge and therefore

cannot interpret it correctly [3,24]. In order to cross

boundaries—either departmental or organizational—

the knowledge needs to be stripped of its context for the

receiving end to be able to understand it [1]. An

interesting distinction can be made here about the

magnitude of this problem in high versus low context

communication environments. High context commu-

nication is defined as one in which much of the

information is embedded in the context—either phys-

ical or personal—and very little information is explic-

itly coded. Low context communication is on the other

end of the continuum, representing messages in which

most of the information is explicitly coded in the

message [10]. Thus, people in low context cultures

will rely more on formal communications that can be

verbally expressed, while people in the high context

cultures will rely on context variables such as individ-

ual background and associations [16]. This distinction

implies that the effective application of technology to

support organizational memory might be greater in

low- context cultures and more challenging in high

context cultures.

A second problem concerns the locations of knowl-

edge. OM generally resides in five different types of

retainers [28]: Individuals, who retain knowledge in

their memory stores or in their belief structures,

values, or assumptions; culture that stores knowledge

in language, shared framework, symbols, and stories;

transformations, procedures, and rules, which include

embedded knowledge such as the logic behind them;

structure and roles that represent the organization’s

perception of the environment, and social expect-

ations; and finally, the physical settings of the work-

place represent knowledge about status hierarchy and

behaviour perceptions. These retainers of OM may be

in different locations and their memories might be

difficult to combine [3,32].

A third problem with OM management is that

knowledge is often tacit. Tacit knowledge is a highly

personal knowledge and is hard to formalize. It is

rooted in action, commitment, and involvement in a

specific context [20]. Tacit knowledge is difficult to

track and maintain in large organizational memories

[25].

A fourth problem concerns the volatility of orga-

nizational knowledge. This volatility results in fre-

quent changes to the contents of the OM [32]. In

addition, combined with the problem of context de-

pendence, the volatility of knowledge further compli-

cates the search and retrieval of knowledge included

in the OM.

Finally, since some knowledge is retained outside

the organization [28] or from unfamiliar sources

within the organization, a measure of the retainer’s

legitimacy and reliability is required [3]. In fact, an

inquirer is more motivated to retrieve knowledge if he

or she is aware of the knowledge and sees potential

value in the knowledge [24]. This information should

be attached to OM to facilitate the retrieval and use of

knowledge.

These five problems create difficulties for members

of the organization in retrieving and using knowledge

that resides in OM. As well, they complicate the

design of the mnemonic layer of an OMIS, i.e., the

layer intended to support the processes involved in

using the OM. As a result, organizations might not be

able to attain the potential benefits of increased

effectiveness and performance that can be associated

with effective OMIS [25].

This paper explores how technology can be used to

overcome the above problems and proposes a con-

ceptual design for an information system intended to

support effective management and use of organiza-

tional memory. We base our approach on the obser-

vation that small workgroups—called communities of

practice—are usually efficient in their communication

and sharing of collective knowledge, even when the

knowledge is tacit [7,8]. Therefore, to gain a better

understanding of possible ways to overcome the

barriers for efficient OM management, we examine

the processes involved in the management of the

collective memory of smaller workgroups. In partic-

D. Nevo, Y. Wand / Decision Support Systems 39 (2005) 549–562 551

ular, we use the concept of transactive memory

systems that has been developed to explain how

individuals in small workgroup form a collective

memory [18,30,31]. We propose what the barriers to

extending transactive memory mechanisms to the

whole organization might be, and suggest how the

use of technology can help to overcome these barriers.

In Section 2 the next section, we review the trans-

active memory literature. In Section 3, we propose an

extension of transactive memory systems to large

groups with the help of information technology. In

Section 4, we examine the potential benefits of such

systems and provide some empirical support for these

benefits. Finally, Section 5 provides some conclusions

and recommendations for future work.

2. The transactive memory approach

A transactive memory system is ‘‘. . .a set of

individual memory systems in combination with the

communication that takes place between individuals’’

([31], p. 186]. Such a system is built on the distinction

between internal and external memory encoding. In

many cases, individuals encode new knowledge in-

ternally, that is —they learn something new and

catalogue it in memory for future retrieval and use.

However, even more often individuals encode knowl-

edge externally either in diaries, in books, or even in

other people’s memory. In these cases, the individual

internally encodes the label (subject) of the knowl-

edge as well as its location, but not the knowledge

itself. Transactive memory systems are built on the

notion of individuals playing the role of external

memory for other individuals who—in turn—encode

meta-memories (i.e., memories about the memories of

others). Knowledge is encoded, stored, and retrieved

through various transactions between individuals.

Three stages are involved in the creation and

maintenance of transactive memory systems: directory

updating, information allocation, and retrieval coordi-

nation [30]. At the first stage, group members create

directories of meta-memories containing information

about the memories held by others. These meta-

memories usually include information about the sub-

ject and location of the knowledge but also—tacitly—

some perceptions about the individual’s own and

others’ expertise on each subject [22].

When new knowledge enters the group, it is

allocated to the person who is perceived by the group

as the expert on the topic. This expertise differentia-

tion can develop naturally within the group or be

imposed by defining roles and allocating responsibil-

ities. For example, a hotel reservation manger is

formally responsible for knowledge related to the

reservations and guests of the hotel. However, she

may also develop an interest in technological innova-

tions and therefore become the informal expert on

new technologies that may be useful for the hotel. In

either case, relevant knowledge that enters the orga-

nization is allocated to her.

Finally, a group member wishing to retrieve some

knowledge will first assess his or her own ‘‘feeling

of knowing’’ on the topic and then—if necessary—

will evaluate other group members that may possess

this knowledge. This again requires some evaluation

of perceived expertise. For example, if the reserva-

tion manager would like to know the credit of a

potential guest, she will probably turn to the hotel’s

credit department for the relevant knowledge.

Initial research on transactive memory focused on

dating couples [12,31] and later extended to small

groups. In group studies, the existence of transactive

memory was measured by assigning groups the simple

task of building the AM portion of an AM/FM radio.

Some of the groups were trained together, while others

were trained individually and assigned to groups after

the training session. In three different experiments, the

results show that training together led to the develop-

ment of transactive memory in the group and also

resulted in improved group performance [18]. An

additional benefit of transactive memory is in creating

a more efficient problem problem-solving mechanism

[17]. Since group members know more about each

other, they are able to match problems with the people

who are most likely to solve them.

While most research on transactive memory focuses

on small groups or intimate couples, some work relates

transactive memory to OM [3]. However, these studies

do not extend a single transactivememory system to the

whole organization, but rather remain within the frame-

work of small groups, for example, by examining the

existence and relations between various transactive

memory systems within organizational memory [3].

To apply the above benefits of transactive memory

to the whole organization, we first examine whether


there is basis to believe that a transactive memory, in

fact, develops in organizations. To this end, we exam-

ine three measures for the existence of transactive

memory: memory differentiation, which addresses the

specialization of group members in specific topics; task

coordination, which reflects the ability of group mem-

bers to work together smoothly; and task credibility,

which is the level of trust between group members in

each other’s knowledge [18].

When organizations are created, formal roles are

assigned to people and groups. These roles create

memory differentiation in the organization. For ex-

ample, in a business school, knowledge of adminis-

tering students is divided between the undergraduate

office, the Masters office, and the PhD office. The

departmental structure of organizations also creates

coordinated tasks and—in many cases—task credi-

bility issues. In other words, using the three meas-

ures, we can view organizations as a workgroup of

smaller groups that work together. In this case, a

transactive memory system develops [3]. Moreover,

often organizations invest in various knowledge-

creating social activities, such as employee educa-

tion, the creation of social networks or brainstorming

activities [4]. Such activities can contribute to the

natural development of transactive memory within

the organization.

It seems, therefore, that the mechanisms operating

in transactive memory systems in small groups

should have been able to support effective OM

management across the organization. Yet, as the

analysis of problems in the previous section points

out, this is not the case. We propose two explanations

to these observations:

1. The meta-memory directory required for people to

allocate and retrieve knowledge from the right

group might simply be too large for the

individual’s memory capacity. This is especially

the case in large or geographically dispersed

organizations, and even more so if we consider

that individuals may be required to possess some

knowledge about members within every subgroup

in the organization.

2. Uncertainty might exist as to who should be the

‘‘owner’’ of certain types of knowledge. In

particular, certain knowledge may not ‘‘‘formal-

ly’’’ belong to any department or to any specific

role in the organization. In such cases, the

knowledge may be allocated to individuals based

on their personal interest or on internal expertise

definitions within workgroups. While such infor-

mal allocations work well within small groups,

they can cause problems when applied across the

organization.

We propose that these two problems—which hin-

der the extension of the transactive memory mecha-

nisms to large groups such as an organization—can

be alleviated with the use of technology and a more

formalized approach to meta-memory directories. In

other words, we propose to use an information

system to support an organization-wide transactive

memory system. Specifically, we identify the role of

technology in the creation and maintenance of the

directories of organizational meta-memories. We sug-

gest that by using technology to support organiza-

tion-wide directories, we can enable individuals to

identify knowledge retainers across the organization

(i.e., outside their own immediate work groups) even

in very large or geographically dispersed organiza-

tions, and thus leverage the benefits of transactive

memory. In the next section, we propose a mecha-

nism for creating such organizational directories of

meta-memories.

3. Technology-enhanced transactive memory

Using the notion that small groups succeed in

effectively utilizing a shared memory, we view orga-

nizational memory as consisting of clusters (commu-

nities) of individual memory retainers described in

Fig. 1.

As previous research had shown, transactive mem-

ory develops within each community and members

hold updated directories about other group member’s

memories [3,18,22]. To extend this view to the

organization, we suggest that a more general directory

of meta-memories should be formed, linking the

different communities and assigning responsibilities

of knowledge assimilation to specific groups (for

example, the sales department is in charge of cus-

tomer knowledge). This directory can also support

knowledge transfer between individuals in different

communities.

Fig. 1. A view of organizational memory.


We begin our discussion of the proposed applica-

tion of transactive memory to the whole organization

by identifying the following three types of knowledge:

1. Role knowledge—this is knowledge that is re-

quired by the definition of the knowledge retainer.

For example, a project manager is required to retain

specific knowledge about projects.

2. Instance knowledge—this is knowledge that is not

required by the formal definition of the knowledge

retainer’s role. For example, the secretary that has

been with the company for year may have

knowledge about former employees or former

experiences of the company that is not required

by her job definition. Individual instances can

therefore have an informal role as knowledge

retainers.

3. Transactive knowledge—this is the directory

knowledge a retainer has about group members.

The availability of transactive knowledge enables

retainers to effectively extend the knowledge

available to them by being able to access their

group members’ knowledge. This knowledge may

be either role or instance knowledge.

In an effective transactive memory system—such

as those that develop within close workgroups—the

transactive knowledge of each retainer will include

references to both the role and the instance knowledge

of all other retainers. However, when extended to the

whole organization, individuals’ transactive knowl-

edge usually will only include partial reference to role

knowledge beyond the immediate workgroup and

likely very little reference to instance knowledge (role

knowledge can be acquired from organizational struc-

ture and from the division of responsibilities between

the various divisions and roles). As our objective is to

use information technology to enhance the individual

transactive memory knowledge and extend it to orga-

nization-wide sources, we propose to create artificial

directories containing transactive knowledge. These

directories will thus provide information about both

the role and instance knowledge of memory retainers

across the organization.

3.1. Artificial directories of meta-memories

Traditionally, there are two main dimensions to the

directories of meta-memories—the subject of the

knowledge and the location of the knowledge [30].

Thus, when new knowledge enters the group, it is

categorized in group members’ memories based on

these two dimensions. In addition to these two dimen-

sions, a third—tacit—dimension also exists that

includes some perceptions of expertise concerning

self and others’ knowledge [22]. Based on this tacit

dimension, new knowledge that enters the group is

allocated to the perceived group’s expert on the topic

and only then are its subject and location stored in

memory. Similarly, an individual who requires knowl-

edge will assess who in the group is likely to have the

knowledge.

To extend transactive memory to a large group

using artificial directories, we therefore need to for-

Table 1

Categories of meta-knowledge

Category Examples References

Conceptual Ontology: set of concepts needed

to describe a domain. Meta-

models: formalized descriptions

of generalized concepts

[14,21,23]

Descriptive Author information, scope of the

knowledge, intended audience,

cost of attaining the knowledge,

format of the knowledge, date

of knowledge, etc.

[5,15,26]

Cognitive Meta memory; meta-cognitive

knowledge—knowledge about

our own knowledge and abilities

[9,31]

Persuasive Source credibility, expertise,

trustworthiness

[11,13]


malize the two dimensions of meta-memories as well

as to substitute for the third dimension consisting of

tacit group knowledge. The latter, in particular, is

intended to overcome four specific problems of for-

malizing meta-memories. First, members in different

groups might not share a set of concepts to describe

the contents of knowledge (needed or available).

Fig. 2. A model of extended m

Thus, the notion of the subject of knowledge needs

to be further formalized. Second, perceptions of

expertise when group members do not know each

other closely should be formalized. Third, it is diffi-

cult or even impossible to keep track of the expertise

of all members in a large group, as members of one

group might not even know about members of other

groups (let alone know about their knowledge). Fi-

nally, what we termed ‘‘instance knowledge’’ above,

might be easy to perceive within a group, but hard to

formalize across the organization.

We refer to the above four issues, which together

comprise information about knowledge available to

individuals, as meta-knowledge. The literature has

addressed various elements of meta-knowledge and

we summarize some of the most common elements in

four categories presented in Table 1.

We propose that the computerized directories of

meta-memory be based on this formalized meta-

knowledge in order to compensate for the lack of

the group’s tacit knowledge. In other words, we

propose to explicate the third (tacit) dimension of

meta-memories using the notion of meta-knowledge.

The diagram in Fig. 2 depicts a simple model—based

eta-memory directories.

2


on the entity-relationship notation—linking the three

meta-memory dimensions of retainers (location),

knowledge (subject), and meta-knowledge.

In this model, retainers of knowledge are charac-

terized by cognitive and descriptive meta-knowledge

(e.g., years of education or perceived self expertise).

These retainers possess knowledge about concepts

and/or instances in the organization—i.e., about sub-

jects of knowledge. The knowledge possessed by

retainers is in the form of predicates (truth statements)

about the state of affairs at a given time, past changes,

or possible changes in a domain of interest. The

knowledge predicates are characterized by descriptive

meta-knowledge, for example, the currency of the

predicate, as well as persuasive meta-knowledge such

as the expertise of the retainer on the specific subject

of knowledge.

The subjects of knowledge (concepts and instan-

ces) can also be characterized by descriptive meta-

knowledge. In addition, knowledge subjects are often

related to other subjects. For example, knowledge

about the concept ‘client’ might be related to knowl-

edge about the concept ‘product’. Some common

types of relations are instantiation, specialization,1 or

complementarities of knowledge (i.e., if you know

how to operate a car, then you also need to know the

traffic rules). The specific meta-knowledge that char-

acterizes this relationship is shown in the model as the

conceptual meta-knowledge that signifies the type of

the relationship that exists between predicates. More-

over, in the context of conceptual meta-knowledge, an

organizational ontology defines the domain of orga-

nizational knowledge, i.e., the concepts about which

knowledge might exist and their relationships. There-

fore, conceptual meta-knowledge is also represented

in Fig. 2 by the ‘concept/instance’ entity itself.

Based on the above view of organizational mem-

ory, our extended directories of meta-memory include

three types of elements and the relationships between

them: subjects of knowledge (i.e., the organizational

ontology), retainers of knowledge, and cognitive,

descriptive, and persuasive meta-knowledge. We

now turn to formalizing these three components to

examine how they can be handled using information

technology.

1 ‘c2’ is a sub-concept of ‘c1’ if the set of properties of ‘c1’ is a

subset of the set of properties of ‘c2’.

3.2. Formalization

We define O as the set representing the organiza-

tional ontology: O={xjx is a term relevant to the

organization}. Effectively, O is the set of terms

needed to describe the universe of discourse of

organizational memory. A term in the ontology may

be a generic concept (e.g., a person), an instance of

another concept (e.g., a specific individual), or a

relationship that might exist between concepts and

or instances (e.g., ‘John is a client’).

In addition to the ontology, the retainer set defines

all the possible memory retainers (based on the five

types of retainers described in Ref. [28]). Again a

retainer can represent a generic concept, in which case

it is termed a Role (e.g., ‘Production Manager’) or it

can be an instance of a role (e.g., ‘Jane, the Marketing

Manager’).

We now define the relation2 knows about: K(x,y),

where x is a subject and y is a retainer. For example:

K(‘Jane’, Client) represents that Jane has knowledge

about the concept Client. Fig. 3 illustrates various

types of the relation ‘‘knows about’’. Formally,

retainers in specific roles are required to know about

concepts and instances defined by their role defini-

tion. Individuals inherit the knowledge requirements

of the roles they play in the organization (e.g., all

individual project managers are required to possess

the basic knowledge that is defined in the job

description of the project manager role). In addition,

Fig. 3. The knowledge relationship.

Generally, a relation between concepts and/or instances is

represented by an n-place predicate that is true and relevant in

the universe of discourse (e.g., ‘‘John works in sales’’!Works

(John, sales)).


individuals may hold knowledge that is not required

by their formal role but that they have acquired

somehow. In transactive memory terminology, this

knowledge is assigned to them because of their

personal interests or because of some informal role

that they have acquired within the group. For

example, a group member in the accounting division

may be assigned to be the group’s specialist on

technological innovations related to the division’s

work. The formal roles played by memory retainers

have an impact on the way knowledge can be

retrieved from organizational memory. Specifically,

the existence of formal division of knowledge

facilitates the retrieval of knowledge in transactive

memory systems [12].

Using the definitions above, we now can create

simple transactive memory queries. For example,

we can query who are all the retainers that possess

knowledge about project ‘x’? Or what knowledge is

retained by a specific retainer ‘r’? Note that these

queries can relate to role knowledge or to instance

knowledge, to concepts or to instances of concepts.

Examples for transactive memory queries enabled by

the knowledge relation are:

� Role knowledge about a concept: What does a

project manager know about ‘‘projects’’? Which

roles possess knowledge about ‘‘clients’’?� Role knowledge about instance of a concept: What

does a project manager know about a specific

project?� Role instance knowledge about a concept: What

does Jane know about ‘‘projects’’? What individ-

uals know about clients?� Role instance knowledge about an instance of a

concept: What individuals know about the client x?

By now we have formalized the two ‘traditional’

dimensions proposed by transactive memory theory:

—the subject of the knowledge and the retainer of the

knowledge. We are able to create a meta-memory

directory as well as basic transactive memory queries

to locate knowledge in organizational memory. How-

ever, as discussed earlier, in order to capture tacit

group knowledge that exists in small groups, we need

to add a third—meta-knowledge—dimension to the

directories of meta-memories. We now turn to de-

scribe this meta-knowledge.

The final dimension in the proposed directory of

meta-memory includes the four types of meta-knowl-

edge described in Table 1. We further distinguish

between two groups of meta-knowledge elements.

The first group includes conceptual meta-knowledge

that represents the knowledge subjects and their

relationships and is represented by the ontology.

This meta-knowledge appears in Fig. 2 as an entity

type representing concepts or instances or as specific

relationships between these entities. The second

group includes descriptors of roles and knowledge

relationships, specifically the cognitive, descriptive,

and persuasive components of meta-knowledge. To

demonstrate, consider the following example:

A consultant wishes to find knowledge on how to

adjust a specific function in an information system.

When asked to select a potential knowledge source

to turn to (among 10 possible sources) the

consultant enquires about the expertise of the

knowledge source in this domain, the accuracy and

validity of the knowledge, and the cost of attaining

the knowledge.

In this example, the consultant (an instance of a

role) is searching for knowledge on a specific instance

of the concept ‘information system’. The meta-knowl-

edge requested by the consultant is specific to the

problem at hand and includes persuasive and descrip-

tive meta-knowledge about the knowledge requested.

The conceptual meta-knowledge is represented here

by the concept ‘information system’ and the instanti-

ation relationship. In addition, the consultant may

wish to know if there is other relevant knowledge

that she should be aware of. This again requires the

use of conceptual meta-knowledge to identify related

concepts and/or instances.

To summarize, the traditional transactive memory

model focuses on two dimensions: the subject and the

retainer of the knowledge. All other information is

assumed to be tacit, in group-members minds. Our

model intends to make this tacit dimension explicit via

the different aspects of meta-knowledge. Therefore,

our meta-memory directory is three -dimensional, as

illustrated by the cube in Fig. 4.

Every cell in the conceptual cube in Fig. 4 repre-

sents a piece of transactive knowledge. For example:

‘‘The hotel reservations manager knows about the

Fig. 4. The extended meta-memory directory.


process of room reservations for large groups’’. Every

cell is therefore characterized by an ordered triplet that

includes subject of knowledge, retainer of knowledge,

and a vector of meta-knowledge components. The use

of ontology as the domain of knowledge subjects

implies that various cells in the knowledge cube are

conceptually tied to each other thus providing addi-

tional meta-knowledge such as knowledge comple-

mentarities or specializations. We claim that using the

cube structure as the basis of the organizational trans-

active memory directories can facilitate updating and

retrieval of knowledge from the organizational mem-

ory. This is explained in the next section.

3.3. Directory updating, information allocation, and

memory retrieval

We follow Wegner [30] to show how the trans-

active memory information system can support the

three defining activities of transactive memory: direc-

tory updating, information allocation, and memory

retrieval. These activities are illustrated in Fig. 5.

As new knowledge enters the organization, it

should be allocated to the right retainer. Using the

knowledge cube, the recipient of the knowledge can

identify the subject of the knowledge and locate the

retainer that has a declared expertise on this topic. The

knowledge can then be allocated to this retainer. The

cube structure enables a very precise allocation of

knowledge. If more than one retainer exist that has a

declared expertise on the topic of the new knowledge,

the allocation of the knowledge can be targeted to the

most suitable retainer by examining the additional

meta-knowledge. For example, many people may

indicate knowledge concerning the company’s prod-

ucts; however, engineering knowledge will be direct-

ed to the production manager while knowledge

regarding competing products will go to the sales

and marketing manager. The knowledge relationship

(‘‘knows about’’) defines the topics in which a spe-

cific retainer is proficient and the organizational

ontology relates these topics to more general areas

of expertise.

Similarly, when an individual seeks some knowl-

edge, they can query the meta-memory directory to

identify the best knowledge for their need. The cube

structure and the transactive memory queries specified

in the previous section support fast retrieval of spe-

cific knowledge from the organizational memory. For

example, we can query the directory for the people

with knowledge about the company’s products. This

in itself may not be different from any other search

engine that exists today. However, using the meta-

knowledge directories, we can then focus the results

on a specific subset proposed by the organizational

ontology (some specialization of the concept ‘prod-

uct’) and reduce the set of results. Finally, we can

select the most suitable source of knowledge by

Table 2

Examples for the use of meta-knowledge in knowledge retrieval

Search goal Search engine

(using keywords)

Transactive memory approach

(using meta-knowledge)

Research a

new topic.

For example,

search for

‘‘research

grant

application’’

Keyword search

brings numerous

results that the

knowledge

seeker needs

to sort through

The ontology (conceptual

meta-knowledge) provides

a set of relevant terms and

the relations among them,

so the knowledge seeker

can refine their search based

on their specific goals. For

example, the search term

‘‘research grant’’ is tied to

‘‘granting agencies’’,

‘‘ethical review process’’,

and ‘‘funding rules’’

Find the best

result from

the search

Results are often

sorted by some

relevance ranking

Results can be sorted by

various criteria based on the

meta-knowledge dimension.

For example, by relevance,

accuracy, or currency of the

knowledge itself, or by

source characteristics such

as background, credibility,

or expertise. The knowledge

seeker can make a more

informed selection of the

knowledge

Fig. 5. Information allocation and retrieval using the meta-memory directory.


examining the additional meta-knowledge. For exam-

ple, if we are looking for knowledge concerning the

sales of a specific subset of our products, we can

query the system for all the retainers of knowledge

about this subset and then select the retainer that we

feel is most suitable to answer this query. To illustrate

how meta-knowledge would improve the retrieval of

knowledge from organizational memory, consider the

example of a researcher looking for information on

how to write a successful grant proposal. Table 2

shows the differences in the search results between

traditional search engines and the transactive memory

approach.

The main challenge posed by this approach is the

ability to keep the meta-memory directories updated.

Some of the updates can be done automatically since

much of the knowledge in the organization is re-

quired by some formal job definitions (as illustrated

in Fig. 3). The updates of expertise on knowledge

that is not formally required by a specific role will

still be the responsibility of organizational members

and cannot be easily automated. Studies on trans-

active memory mechanisms in small groups indicate

that groups discuss and encode much of the trans-

active knowledge at the early stages of their work. As

the work progresses, the groups have additional

encoding cycles that are initiated by questions about

a task and are followed by the identification and

encoding of relevant experts and coordination of this

new transactive knowledge with previous knowledge

[22]. Following this, we propose that the automated

transactive memory will be set initially to reflect

Table 3

Alleviating the problems associates with OM management

Problem with OM Proposed solution

Knowledge in the OM

is contextualized

Conceptual meta-knowledge

can help reconstruct the original

context of the knowledge

Retainers of OM may be

in different locations

and their memories might

be difficult to combine

Descriptive meta-knowledge

locates different knowledge

retainers as well as provides

information on the most up-to-

date version of the knowledge

Knowledge may be tacit Tacit knowledge can be

located and evaluated using

meta-memory and the four

types of meta-knowledge

The content of OM

changes often

The responsibility to ‘‘keep

track of knowledge’’ is now at

the hand of the relevant expert.

The system maintains only

meta-memory, which is less

volatile than the knowledge itself

Knowledge seekers require Descriptive and persuasive


existing knowledge, and then will be updated accord-

ing to the encoding cycles in the various groups. We

also note that the volatility of meta-knowledge is likely

to be lower than the volatility of knowledge itself.

Hence, periodical (rather than continuous) updates

should not diminish considerably the effectiveness of

the system.

A second challenge for encoding transactive

knowledge relates to the combination of memories

of different groups within the organization and the

resolution of conflicting knowledge between these

groups. The existence of ontology in the design of

the system can resolve some of these problems by

identifying related concepts and preventing the ambi-

guity of concepts. Furthermore, it can be used to

identify different instances of knowledge about the

same concepts. However, the decisions on resolving

conflicting knowledge instances are a matter of man-

agerial practices.
a measure of the retainer’s
legitimacy and reliability

when retrieving knowledge

meta-knowledge is included in

the meta-memory directory

4. Discussion

The purpose of the model described above is to

demonstrate the ability of information technology to

extend the notion of transactive memory to large

groups. Using technology we can create computer-

supported knowledge allocation process that is based

on the meta-knowledge provided about each of the

knowledge retainers. Similarly, the system can assist

in the retrieval of knowledge from organizational

memory.

We claim that using information technology as

suggested here can help alleviate some of the prob-

lems of managing organizational memories described

in Section 1. To show this, we present in Table 3 the

set of problems described earlier and explain how a

transactive memory information system can help

alleviate them.

An additional benefit from using the transactive

memory approach is in its potential benefits for group

performance. We claim that the use of meta-memory

will lead to improvement of knowledge adoption due

to its effect on knowledge transfer from organization-

al memory to individual users. To demonstrate this,

we use the notion of ‘‘‘knowledge stickiness’’’, a

measure of the difficulty of transferring knowledge

[27].

Studying knowledge transfer in organizations, Szu-

lanski [27] identified eight predictors for knowledge

stickiness. These predictors concern characteristics of

the source of the knowledge, the recipient, the con-

text, and the message (knowledge) itself. The predic-

tors were measured in the settings of best practices

transfers within organizations and the most significant

predictors of stickiness were the inability to pinpoint

the reasons for a success or failure of replicating

knowledge (causal ambiguity) and the recipient’s lack

of ability to identify, value, and apply knowledge

(absorptive capacity). Other significant factors were

the perceived utility of the transferred knowledge,

perception of source as unreliable, lack of motivation

of source and recipient, lack of retentive capacity of

recipient, unsupportive organizations, and distant re-

lationship between parties.

We suggest that by exposing the receivers of

knowledge to some knowledge about the knowledge

(meta-knowledge) before the knowledge transfer takes

place, it is possible to reduce stickiness. For example,

using meta-knowledge, we hope to provide individu-

als with information that will enable them to select

knowledge that they can interpret most easily based


on their prior knowledge, thus increasing their absorp-

tive capacity. Similarly, the availability of persuasive

meta-knowledge can increase perceived reliability of

the knowledge source.

4.1. Empirical support

Several studies exist that provide empirical support

to the potential benefits of the transactive memory

approach and specifically—the use of meta-knowl-

edge to support the management of organizational

memory. In this last section, we describe some of

these studies as well as propose research questions for

future empirical work.

The first group of empirical studies examines the

benefits of transactive memory in a group setting.

These studies show that transactive memory naturally

develops in groups that train together, and that the

existence of transactive memory leads to improved

group performance and better problem problem-solv-

ing mechanisms [17,18,22]. These early studies on

transactive memory used observations as the measure-

ment method and determined the existence of trans-

active memory using three specific measures: memory

differentiation, task coordination, and task credibility.

A more recent study demonstrated the development of

transactive memory in virtual teams and the positive

effect of this transactive memory on the team’s

performance [33]. Transactive memory was measured

by a three three-item scale, asking respondents about

their perceptions of the team’s transactive knowledge.

This study provides important support for the ideas

presented in our paper as it identifies the development

of transactive memory in the context of computer-

based communications.

A second group of studies providing support for

technology-supported transactive memory looks at

the potential benefits of meta-knowledge for knowl-

edge adoption in organizations. These studies dem-

onstrate the importance of cues, such as source

credibility, for information adoption [29]. In addition,

they empirically identify the specific knowledge and

source attributes that should be included as meta-

knowledge (cues) in order to increase the likelihood

of knowledge adoption [19]. These knowledge and

source attributes mainly fall under the descriptive

and persuasive meta-knowledge types described ear-

lier in our paper and include such items as the

accuracy and currency of the knowledge and the

trustworthiness, knowledgeability, and willingness-

to-help of the knowledge source. Finally, the studies

show that the probability of information seeking will

increase when the seeker is able to identify what

other people know, when the seeker is able to

evaluate the other person’s knowledge, and when

the seeker can gain timely access to the other person’s

knowledge [6].

Following these studies and the conceptual ap-

proach presented in our paper, we propose that future

empirical studies examine the following questions:

(1) Can technology enable the creation of transactive

memory in cases where it does not develop

naturally?

(2) Will this artificially created transactive memory

lead to the same benefits—namely improved

performance and better problem problem-solving

in the organization—as it does in small groups?

The studies described in this section set the ground

for answering these two questions by defining meas-

ures of transactive memory and performance as well

as by identifying the meta-knowledge that would

effectively influence the information adoption deci-

sion of individuals. This meta-knowledge was pro-

posed in our paper as the third dimension of the meta-

memory directory. The model proposed in the current

paper can provide guidance to future empirical stud-

ies, in particular in suggesting experimental settings.

First, we develop the specific design of the organiza-

tional memory system and the three-dimensional

directories of meta-memory to be tested. Second, we

distinguish between three types of knowledge—e.g.,

role knowledge, instance knowledge, and transactive

knowledge—that are related to the development of

transactive memory. Specifically, we propose that the

existence of instance knowledge might inhibit the

development of transactive memory in settings where

this knowledge is not easily available to all group

members. We expect that in settings where instance

knowledge cannot be fully obtained an information

system based on the transactive memory approach

proposed here would improve the sharing of knowl-

edge. This prediction can be tested empirically by

creating situations in which transactive memory

would not develop naturally by controlling the avail-


ability of instance knowledge to group members and

testing the effect of a system based on the principles

proposed in this paper.

5. Conclusion

In this paper, we have addressed the use of infor-

mation technology to obviate the problems involved

in the use of organizational memory. We suggest an

approach to the design of the memory-supporting

(mnemonic) layer of an organizational memory infor-

mation system. Our approach is rooted in transactive

memory theory, that is, in a theory of collective

memory of small groups. Specifically, we suggest that

the role of technology is to enable the extension of the

transactive memory mechanisms to the whole organi-

zation. The architecture we propose is based on three

dimensions of meta-memory. First, the two ‘‘tradi-

tional’’ dimensions of transactive memory—subject

and retainer. Second, as a replacement to the tacit

aspect of meta-memory, we propose the use of a meta-

knowledge dimension that includes three components:

descriptive, cognitive, and persuasive. These compo-

nents formalize, respectively, what the knowledge is

about, what the individual believes they are capable of

knowing, and what the individual knows about others’

knowledge and expertise. The three components,

when included explicitly in an OMIS can serve to

help allocate and retrieve knowledge more effectively

by informating individuals in the organization. In

addition, the availability of these components of

meta-knowledge can serve to reduce stickiness and

to improve knowledge transfer.

We believe the justification for this approach is

that it provides technology support for existing

organizational mechanisms. The use of a rich set

of meta-knowledge components also provides a

possible solution to the difficulties of knowledge

search and retrieval. The use of ontology has been

shown in various projects to be useful for the

preservation of the context of knowledge and thus

can facilitate an efficient management of organiza-

tional memory. Finally, we have pointed out that

existing empirical studies provide support for the

potential benefits of our approach and proposed

empirical work that will explicitly test the proposed

design.

Acknowledgements

The research was supported in part by a grant from

the Social Sciences and Humanities Research Council

of Canada.

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Dorit Nevo is an assistant professor of

Information Systems at the Schulich

School of Business, York University, Tor-

onto, Canada. She received her PhD in

Management Information Systems from

the University of British Columbia, her

MSc, in Economics from the Technion,—

Israel Institute of Technology, and BA in

Economics and Business Administration

from the University of Haifa, Israel. Her

current research interests include require-

ments analysis, and design and evaluation of Knowledge Manage-

ment Systems.

Yair Wand is CANFOR Professor of MIS

at the Sauder School of Business, The

University of British Columbia. He re-

ceived his DSc in Operations Research

from the Technion,— Israel Institute of

Technology, his MSc in Physics from the

Weizmann Institute, —Israel, and his BSc

in Physics from the Hebrew University,

Jerusalem. His current research interests

include theoretical foundations for infor-

mation systems analysis and design, de-

velopment and evaluation of systems analysis methods, and

conceptual modeling.

organizational memory information systems: a transactive memory approach

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