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Do organizational memory and information technology interact
to affect organizational information needs and provision?
1
,
2
Mohamed El Louadi
Institut Supérieur de Gestion
University of Tunis - Tunisia
and
Imen Tounsi
Hautes Etudes Commerciales
University of Sousse - Tunisia
August 2007
Abstract
The results reported in this paper were obtained through the study of 43 work-units belonging to
five business firms in a large group of Tunisian companies. Using the declarative, procedural
and judgmental dimensions of organizational memory, interaction effects were detected between
IT and organizational memory. Analyses of the data support the view that storage technologies
interact with declarative memory contributing to reduce organizational information needs. But,
contrary to expectations, storage technologies interact negatively with declarative memory on
information provision. Furthermore, network technologies interact negatively with judgmental
memory on information provision. These results raise issues that have been rarely encountered
in the literature.
Keywords:
Organizational Memory, Information Technology, Information Needs, Information
Provision, Tunisia
1
An early draft of this paper has been presented at the First International e-Business Conference, held in
Hammamet (Tunisia) on June 23-25, 2005.
2 This paper is being reviewed for publication in an international peer-reviewed journal. Do not cite without
permission from the first author.
1
Do organizational memory and information technology interact
to affect organizational information needs and provision?
Abstract
The results reported in this paper were obtained through the study of 43 work-units belonging to
five business firms in a large group of Tunisian companies. Using the declarative, procedural
and judgmental dimensions of organizational memory, interaction effects were detected between
IT and organizational memory. Analyses of the data support the view that storage technologies
interact with declarative memory contributing to reduce organizational information needs. But,
contrary to expectations, storage technologies interact negatively with declarative memory on
information provision. Furthermore, network technologies interact negatively with judgmental
memory on information provision. These results raise issues that have been rarely encountered
in the literature.
Keywords:
Organizational Memory, Information Technology, Information Needs, Information
Provision, Tunisia
Introduction
Internal organization’s information-processing capacity has almost always been related to
structural and technological mechanisms (Girod, 1996; Huber, 1990; Cummings and Cross,
2003; Walsham and Barrett, 2005). Quicker and easier access to external information and
knowledge is becoming increasingly more important to organizations. Since the 1990s the
accumulation of data and information in organizations files and databases led researchers’
interest to the study of organization memory too (Souren et al., 2004). Organization memory has
become an additional mechanism allowing organizations to store, process, and disseminate
information with the aim of speeding up organizational learning (Child and Rodrigues, 2001;
Cohen, 1991).
Unfortunately, there has been very little empirical research on organizational memory and its
relationship with the amounts of information needs and provision to date, despite the increasing
realization that organizations are becoming more knowledge-based, relying not only on their
computerized information systems but also on information and feedback from workers,
customers, and partners. Even so, the knowledge-based company depends increasingly on
knowledge, i.e., patents, processes, management skills, old-fashioned experience, past failures
and successes (Levitt and March, 1988; Walsh and Ungson, 1991). This is especially true in the
case of organizations whose members are specialized in some particular task and where
learning occurs essentially by doing. Such companies have managers who need to access more
information about more aspects of the business, from more parts of the organization, and in
shorter time spans (Huber, 1984).
While organizations develop uncertainty-reduction mechanisms by increasing their information-
processing capacities favoring the acquisition, creation, and flow of new information (Galbraith,
1977), some other mechanisms are needed for the processing of information that the
organization already possesses in order to foster learning. Some of the knowledge needed is
accumulated in databases and archived documentation but the most important part lies in
people’s heads (Nonaka, 1995). An organization’s knowledge capacity is therefore a function of
the sum of everything everybody in the organization knows (Aschcraft, 1994; Walsh and
Ungson, 1991).
Organizations do not need knowledge about past events only. They also need knowledge about
past and present happenings and experiences. Learning cannot be dissociated from memory
(Lehner et al., 1998, Walsh and Ungson, 1991); it is “…a process that involves the discovery,
2
retention, and exploitation of stored knowledge” (Moorman and Miner 1998, p. 705).
Mechanisms related to accumulated information about past and present events are collectively
known as the organizational memory (Walsh and Ungson, 1991; Stein and Swass, 1995).
This research endeavors to explore relationships between information technology (IT) and
organizational memory, and their combined effect on the provision of information. It aims at
answering the question as to whether organizational memory is associated with the degree of
information availability and, if so, whether it is augmented by IT in providing needed information.
We have organized this paper as follows. First, we present a definition of organizational memory
and three of its commonly used dimensions: declarative memory, procedural memory, and
judgmental memory. Second, we present a conceptual overview of the concepts. Then we
introduce the method and data collection procedure. In the following section, we present the
measures we used. Following this, we present the results of the tests of the relationships
between the variables which we also discuss then we conclude the paper with the limitations of
the study and propositions for future research.
Organizational Memory
Building on Walsh and Ungson (1991), Stein and Swass (1995) define organizational memory as
“the means by which knowledge from the past is brought to bear on present activities” (p. 22).
Organizational memory has been conceptualized theoretically in several different ways. Ashcraft
(1994), for example, classifies the different types of memories as episodic (knowledge of events
personally experienced by people), semantic (factual knowledge), or procedural (skills learned,
or as Markus (2001) calls it, “best practice”). Girod (1995) defines organizational memory as a
set of competencies associated with beliefs and declarative and procedural knowledge borne out
of inter and intra-organizational structural arrangements.
Synthesizing several literatures, Girod (1995, 1996) distinguishes between three memory
categories. The first, called “declarative memory”, is a mostly explicit memory containing
knowledge accumulated in human memories about facts, things and events. The second,
“procedural memory”, is mostly tacit and contains knowledge about how to do things. And the
third, “judgmental memory”, contains memories related to the individual’s experience.
Taken at the organizational, collective level, declarative and procedural memories are well
known constructs in other management literatures (Anderson, 1983, Moorman and Miner, 1998)
and to cognitive psychologists (Chase and Simon, 1973; Singley and Anderson, 1989). For that
reason, organizational memory will be taken as composed of its three categories: declarative,
procedural, and judgmental, which, according to Girod (1995) can also be conceptualized at the
collective level as well.
Declarative Memory – The Know What
Declarative memory is the sum of technical, scientific, and administrative knowledge detained by
organizational members which is related to their work and which, therefore, should be made
available to the organization (Girod, 1996). It consists of explicit knowledge, i.e., facts,
propositions, events, situations, etc. (Moorman and Miner, 1998). Thus what individuals learn in
school about the operation of machinery and which they bring into the organization upon their
hiring is declarative knowledge. This knowledge can be stored in the individuals’ memory or in
archives, in the form of how-tos that other individuals can tap into. Girod considers that the
memory containing declarative knowledge is not limited to individuals. It can be derived from the
interaction of two or more people. In this case, it is considered collective declarative memory. It
can be formalized and stored in databases for example (centralized collective declarative
memory) or informal, implicit, unrecorded, and volatile (decentralized collective declarative
memory).
At the collective level, declarative memory can be likened to what Walsh (1995) terms as
“shared information”. Moorman and Miner (1998) note that a key characteristic of declarative
3
memory is the diversity of uses to which it can be put thus providing the basis for transfer of the
same knowledge between different applications.
Procedural Memory – The Know How
Procedural memory is composed of the know-how that individuals apply in their day-to-day work-
life (Cohen and Bacdayan, 1994). It is skill and action knowledge (Moorman and Miner, 1998).
Unlike declarative knowledge, which is stored in declarative memories, procedural knowledge is
the result of an individual’s personal learning experience. A learning organization tries to
transform this knowledge into organizational knowledge to make it available to everyone (Girod,
1996). Routine knowledge transformed into procedural knowledge is stored into rules and
procedures (Cohen and Bacdayan, 1994) and is categorized as centralized collective procedural
memory by Girod (1995). Moorman and Miner (1998) note that procedural memory generally
becomes “automatic” or that it is accessible “unconsciously” (p. 708). Most often tacit, procedural
memory can, however, be made explicit when it is documented and circulated in the shape of
procedures, for example.
Judgmental Memory – The Know Why
Judgmental memory is the individuals’ tendency to interpret information, events, and knowledge
to derive proper action. It is memory about why things are done. Judgmental memory, also
called “rationale memory” by Moran and Carroll (1996), relies forcibly on individuals’ own
experience and knowledge. It is what makes the opinion of an expert more valuable than a
layperson’s. It is also the type of memory that suffers the most from personnel turnover because
it is very hard to extract and record. At the collective level, judgmental memory constitutes the
sum of all organizational members’ judgmental memories and the unique way that an
organization senses and interprets events.
Organizational Memory and IT
Memory is increasingly being regarded as a resource, like labor and capital. In that, it is on the
same path as information. In the information-processing view, an organization is viewed as an
ensemble of information-processors (humans, machines, networks, etc.) matching information
and knowledge acquired from the outside with information and knowledge accumulated in order
to improve decision-making and effectiveness.
In an ethnographic study of a help line group, Ackerman and Halverson (2000) demonstrated the
theoretical limitations of the metaphor of a single organizational memory. They contend that
there is a supra-individual memory, maybe even several memories, complexly distributed among
several people and technologies. Walsh and Ungson (1991) consider memory to include not only
people but also archives, organizational procedures, organizational structures, and culture, but
not information technology. In their model, Walsh and Ungson (1991) have categorized
organizational memory as being spread over six organizational contexts: individuals (people’s
heads), culture, organizational transformations, structures, organizational ecology, and external
archives. Ackerman (1996) argues that information repositories such as corporate manuals,
databases, filing systems, and even anecdotal stories could also be included in the construct of
organizational memory.
Yet, one of the objectives of IT is to make the required information easily accessible. IT plays an
important role in disseminating information and in facilitating communication within organizations
(Huber, 1990; Walsham, 2001). Like Huber (1990 p. 65), our hypothesis is that use of IT should
lead to more information availability and greater information accessibility.
It can also be easily argued that IT represents a way for organizations to augment their
organizational memory (Ackerman, 1996; Lehner et al., 1998; Moorman and Miner, 1998). As a
consequence, IT would become embedded in a broader conceptualization of organizational
memory as contended by Watson (1996) who considers organizational memory to be essentially
4
technology driven, a comprehensive enterprise-wide database supported by multimedia,
imaging, and electronic archiving and document management systems.
Conversely, a distinction can be made between memory that is based on IT, also called
organizational memory systems (OMS) (Ackerman, 1996; Lehner et al., 1998), and
organizational memory information systems (OMIS) (Wijnhoven, 1999). While Walsh and
Ungson (1991) did not count computer files and databases among their components of
organizational memory, Wijnhoven (1999), for example, includes in it individuals, culture,
transformation, structure, ecology, external environment, computer-based information systems,
and non-IT based records and files. Consequently, there would be two types of memories, one
that is based on computer and communication technologies and another which is based on non
IT-based mechanisms, both hypothesized to contribute positively to organizational information-
processing capacity. As noted by Ackerman (1996):
“Organizational memory systems (OMS) offer the possibility that computer systems
can better serve the information storage and retrieval needs of an organization’s
memory than can present technical and social methods.” (Ackerman 1996, p. 10).
Non IT-based memory, especially that which lies in people’s heads has the advantage of being
available and relatively more accessible within a known context, but it suffers from poor retention
and is volatile because it is prone to leaving the organization once the individual holding it leaves
(Stein and Zwass, 1995) causing what Borghoff and Pareschi (1997) and Kransdorff (1998) call
“corporate amnesia”. Thus, non-computer based memory can suffer corruption, decay in both
detail and accuracy or even erasure with time. Knowledge in people’s heads comes and goes as
people come and go (Nonaka, 1995).
IT-based memory, on the other hand, is quasi-permanent; knowledge is logged, indexed,
secured, and organized in such a way that it becomes accessible. However, IT-based memory
suffers from limitations that have been pointed out by Ackerman (1996) such as the impossibility
of having a unified organizational memory reflected in incomplete, fragmented and/or
overlapping databases and files. Furthermore, IT often lacks the capability of providing
necessary clues in light of the context in which memory is found most useful.
IT contributes to organizational memory in at least two ways: by making accumulated knowledge
accessible to organization members or by making individuals with knowledge known (Ackerman,
1996; Jennex, 2006). However, there is still no agreement as to which technologies best support
this memory and Lehner et al. (1998) suggest that organizational memory cannot be served by a
single technology. Cross and Baird (2000) contend that it is not enough to accumulate
information and knowledge in electronic repositories and that organizational members rely upon
a network of relationships for information and advice. According to Cross and Baird (2000),
people take advantage of databases only when more trained colleagues point them to a specific
location in the database where they can find the information that they seek. For Cross and Baird,
IT is only one form of memory that organizational members tap into when solving problems and
its use is therefore limited.
In this paper, we consider, like others (Jennex, 2006; Huber, 1991; Lehner et al., 1998; Stein
and Zwass, 1995), that IT is also used to support organizational memory.
Setting
The study was conducted in Tunisia in 2002. Tunisia is a small 10 million-people North-African
country. In 1995, it became the first Maghreb and Arab country to sign an association agreement
with the European Union. Since then, Tunisia’s economy has grown by over 4.5% annually.
Three years later, it ratified the European Association Agreement which calls for the gradual
5
removal of all tariffs on industrial goods by 2008. Today, Tunisia is seriously preparing its
industrial sector, composed of more than 10,800 firms of more than 10 employees, to
international competition through a $2.5 billion competitive restructuring program, launched in
1995 and dubbed ''The Way to Competition''. More than 2,360 Tunisian firms are totally
exporting, and this number is increasing. These firms face the challenge to be as competitive as
their European counterparts, maybe even as their other Asian and American partners.
Conscious of these implications, and encouraged by a set of governmental policies, the
computer and telecommunication sectors have greatly contributed in making Tunisia an ideal
regional telecommunications hub with access to Europe, the Middle East and Africa. More than
TD 1779 million were invested in IT as part of the 10
th
Plan (2002-2006)
3
and TD 3107 million
are planned in the 11
th
five-year Economic and Social Development Plan (2007-2011).
According to an International Herald Tribune article (Stratte-McClure, 2000), “Advances in
telecommunications, the Internet and electronic commerce are appropriate symbols of Tunisia's
industrial, social and economic strides”. Having been the first African and Arab country to
connect to the Internet in 1991, when there were only thirty-one countries connected (ITU,
2003), Tunisia now boasts more than 1 446 000 Internet users (roughly 14.5% of the population)
4
.
In 2005, Tunisia was ranked 31
st
according to the Network Readiness Index developed by the
World Economic Forum (WEF), up from the 40
th
position it was in the previous year (Forbes,
2005). It was ranked No.1 in Africa and in the Arab world for economic competitiveness in the
2007 WEF Global Competitiveness Report. Based on an assessment of the economies of 128
countries, the report ranks Tunisia the 29
th
most competitive country in the world. Tunisia was
also ranked by the WEF as the first Arab and African country and 35
th
in the world in the field of
global information technology
5
. Tunisia is currently working out an overall IT strategy for the
2007-2011 period with the support of the World Bank, with an aim of reaching an IT
infrastructure equivalent to that of the developed countries by 2011.
However, even though Tunisia has often been touted by the International Monetary Fund (IMF)
and the World Bank as models for its emerging economies, IT, the main driver for its integration
into world economy, seems to have been mostly adopted by the industry for clerical purposes.
With a few exceptions, like the group of companies we studied.
Data Collection
The group of firms in which we conducted our study was created in 1967, 11 years after
Tunisia’s independence. In its beginnings, it was specialized in commercializing meat products
such as chicken and turkey. In three decades, it expanded into a Holding composed of 30 firms
organized in a matrix form and employing more than 6.000 people. Today, 95% of the Holding’s
products are either new in Tunisia (such as industrial ceramic) or manufactured using new
technologies. It exports some of its products to more than 35 countries. Highly modernized,
having complied with most ISO 9000 and restructuring programs, the group is reputed for its
sense of organization, processes and procedures, overseen by a central audit structure in
headquarters.
It was that central audit unit that selected the companies as well as of the work-units within them
which were to participate because the study was incorporated into a larger scale survey which
was being made simultaneously. The only condition was that the questionnaire, written in
3
See The Tenth Development Plan, page 130, http://www.tunisieinfo.com/10plan-fr.pdf, last accessed 9 April 2005
(available in French only).
4
As of this writing,
March 2007, see the Tunisian Ministry of Technologies and Communication,
http://www.infocom.tn/index.php?id=163
and
http://www.infocom.tn/uploads/media/Statistiques_internet_fin__Mars_2007_02.xls
, last accessed 16 August 2007.
5
See http://www.weforum.org/pdf/gitr/rankings2007.pdf, last accessed 23 August 2007.
6
French, that we used for data collection be handed to the same units across firms. The firms
were geographically dispersed in four cities. The units in each firm were: (1) Production, (2)
Commercial, (3) Maintenance, (4) Accounting, (5) Finance, (6) Quality Assurance, (7) MIS, (8)
Purchasing, and (9) Administrative and HR. The major focus of this study is on organizations
work-units’ memory and information needs and provision. We therefore concentrated on
collecting data from various work- units in five firms all belonging to the same group of
companies.
Because the use of multiple informants is ideal while measuring organization-level constructs
(Bruggen et al., 2002), we polled several informants from each work-unit. While the use of
multiple informants from each work-unit is preferable, the single informant approach allows for a
larger number of work-units to be surveyed. In the face of resource constraints, we opted for the
latter approach. Consequently, we took the precaution of wording our questionnaire so as to
make clear that the entire organization is to be considered
6
.
Our starting random sample of 45 (5 firms x 9 units) was reduced to 43 because two work-units
did not respond in time or produced unusable answers. Forty three responses will consequently
be used for analysis in the remainder of this paper (Table I).
Table I. Sample Characteristics.
Main activity No. of Work-units #. employees (FTE)
1 Animal food industry 9 156
2 Animal food industry 9 48
3 Food industry 9 157
4 Food industry 9 324
5 Manufacturing 7 288
Total 43
The Measures
Measures of organizational memory, IT penetration and information needs and provision were
used for this study. These measures are explained below.
Organizational Memory
A measure composed of 15 items was specially designed for this study to measure
organizational memory. Factor analysis yielded a three factor solution explaining 64% of the
variance. Coinciding with Girod’s (1995) three dimensions, the factors were labeled (1)
Procedural Memory, (2) Judgmental Memory, and (3) Declarative Memory (see Table II).
6
We refer the interested reader to Hage and Aiken's (1967) discussion on this subject and notably to footnotes 7 and
8 on page 76.
7
Table II. Item-to factor loadings for the Organizational Memory Variable.
Procedural
Memory
Judgmental
Memory
Declarative
Memory
Existence of documentation concerning past successful
projects
.81
Existence of documentation concerning past failed projects
a
.79
Existence of a procedure assuring the replacement of a
leaving manager by another
.79
Number of qualified or specialized members in the unit .48
The extent to which experimented unit members are
solicited for help and advice
.79
The extent to which help is available when an
administrative problem occurs within the unit
.76
The extent to which help is available when a technical
problem occurs within the unit
.71
The extent to which help is available when a
social/relational problem occurs within the unit
.71
Frequency of individual activity reports production .95
Frequency of group activity reports production .92
Frequency of meetings within the unit .66
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaise
r
Normalization.
a
Reverse scored
Amount of Information Needs and Provision
Information needs and provision of any organization can be classified as internal or external.
Internal information is generated within the organization to satisfy its working members and
decision-making functions. It pertains to the organization’s internal operations. It supports
decisions typically made by operations managers with short time horizons. External information
is information that is of interest for the organization but which originates in its environment. It
pertains to the organization’s customers, competitors, etc. (Ewusi-Mensah, 1981).
Respondents were asked to rate, on a scale from 1 (not at all) to 5 (a lot), the extent of
availability of 10 categories of external information and 9 categories of internal external
information. These measures were developed by El Louadi (1996) and their reliability and
dimensionality were later further reassessed (El Louadi, 1998).
Degree of IT Adoption
Information technology refers to the technologies and applications which combine the
information processing, storage and transmission powers of computers with the distance-
transmission capabilities of telecommunication technologies (Bakopoulos, 1985). It also
complements and supports knowledge processing (Tuomi, 2000). From our previous discussion,
IT can also be conceptualized as a mechanism helping to augment organizational memory.
Some technologies, such as electronic filing cabinets, document archiving systems, relational
databases, Intranet, groupware, data warehouses, navigators’ information archiving with
bookmarks, etc. have more of a memory focus than others. Unfortunately, there is still little
evidence supporting the preeminence of some technologies over others with regards to
organizational memory.
Shortly after its creation, the group in which we conducted our study was using a centrally
controlled IT infrastructure with several systems and computer centers disseminated across the
units. In the mean time, the group had diversified its activities to include eggs, ice cream,
margarine, yogurt, wood, refrigerators, computer assembly, mufflers, tourism, etc. In 1991, it
shifted towards clients-server computing progressively harmonizing its information systems until
it adopted an ERP in 1998. In less than five years, it moved from unified transaction-processing
8
to reporting to on-line analytical processing thus acquiring and fully exploiting a huge data
warehouse fed by the many data marts scattered over the units. As a result, the group is
probably one of the most, if not the most, developed IS shop in the Tunisian industry today. It
uses electronic mail extensively (1.200 accounts at the time of the study) and hires its
employees through its Web site.
For this reason, we included all technologies available in the business units we surveyed.
In the questionnaire, we asked questions concerning the degree of adoption of IT using a 26-
item list of information technologies. The respondents were asked to rate each technology on a
scale from 1 (technology not operational) to 5 (operational on a widespread basis). Factor
analysis with varimax (orthogonal) rotation and Kaiser normalization was then performed with
the purpose of generating factors that are easily interpretable. A four -factor solution emerged
which explains 66% of the scale’s variance. As shown in Table III, the factors were labeled (1)
Software Penetration, (2) Storage Penetration, (3) Network Penetration, and (4) Communication
Penetration.
Table III. Item-to-factor loadings for the IT Variable.
Software
Penetration
Storage
Penetration
Network
Penetration
Communication
Penetration
Accounting Software
PC Software
Inventory Mgmt. Software
.79
.75
.69
Personal Information Managers
Personal Computers
Databases (Access)
Data warehouse
.78
.77
.59
.47
Fax
Voice Mail
Wide Area Networks
.74
.74
.69
External (Internet) e-mail
Internal (Intranet) e-mail
.85
.53
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
Analyses
Prior to analysis, the IT (software, storage, network, and communication) variables, the memory
(procedural, judgmental, and declarative), and the information provision (external and internal)
and information needs (external and internal) variables were examined through various SPSS
programs for accuracy of data entry, missing values, and normality and multivariate analyses.
Because of the small size of our sample, we conducted tests of normality of variables following
Tabachnick and Fidell (1989) recommendations by using descriptive programs for skewness.
We found moderate negative skewness for the external information needs variable (skewness=-
1.26). We corrected for skewness by computing the square root of the reflect of that variable.
This reduced skewness considerably
7
.
We calculated the Shapiro-Wilk statistic W (Shapiro and Wilk, 1965), which has become
standard for small samples with 50 or fewer observations (Royston, 1982). The Shapiro-Wilk test
revealed that the hypothesis of non-normality could not be rejected for 4 out of 7 independent
variables and 2 out of four dependent variables (W varying between .84 and .94 significant at
7
The reflect of a variable is obtained by deducting the scores from the largest value incremented by Tabachnick and
Fidell (1989). Because the scale on which the External Information Needs variable was measured ranges from 1 to 5,
we used the following transformation formula: transf=sqrt(6-x).
9
p=.024 or less).
We also looked for multivariate outliers. The tests revealed the existence of 11 multivariate
outliers for which the Mahalanobis distance was greater than 3. Given the size of the data set,
we were reluctant to eliminate them. However, we flagged the outliers with a dummy variable
(see Tabachnick and Fidell 1989, p. 69) and applied the Shapiro-Wilk test on the remaining
observations (the reduced sample). Thus, there were only three independent variables for which
normality remained an issue (W≥.880; p≤.015).
Though the unit of analysis is the business unit, not work-units or individuals, aggregating the
data within work-units could present methodological issues for which there are yet no
satisfactory solutions if members within a work-unit perceive the dimensions studied here
differently. To test the assumption that participants from each work-unit responded similarly, a
series of ANOVAs was performed (Dixon and Massey, 1969). Because we observed large
variances among individuals making up the groups and the way they are responding to the
variables, the decision was not to pool individual responses to represent groups.
Table IV summarizes the statistical properties of the variables used in this study.
Table IV. Statistical Properties of the Variables of the Study.
Min Max Mean Std-Dev α
Procedural Memory 1.00 4.75 3.32 .97 .75
Declarative Memory 1.00 5.00 2.97 1.04 .76
Judgmental Memory 2.00 5.00
3.65
.81 .83
Software Penetration 1.00 5.00 4.12 1.11 .67
Storage Penetration 1.40 5.00 3.97 .94 .70
Network Penetration 1.00 5.00 3.10 1.29 .63
Communication Penetration 1.00 5.00 4.31 .95 .65
Internal Information Needs 2.00 5.00
3.89
.84 .88
Internal Information Provision 1.00 4.44 3.38 .81 .87
External Information Needs 1.00 5.00 3.63 .93 .89
External Information Provision 1.00 4.00 2.73 .73 .86
T-tests revealed that though the need for internal information is not significantly greater than the
need for external information, the provision of internal information is significantly greater than the
provision of external information (t=5.59, 42 df, p<.0001) (see Table IV and Figure 1).
Furthermore, the need for information is significantly greater than provision whether it is internal
(t=4.06, 42 df, p<.0001) or external (t=6.15, 42 df, p<.0001). The least we can infer from this
result is that work-units in this sample do not suffer from information overload but rather from
information poverty (Simon, 1982).
10
External
information
provision
2.73
Internal
information
provision
3.38
External
information
needs
3.63
Internal
information
needs
3.89
3.06 3.75
Mean
information
provision
Mean
information
needs
Figure 1. Statistically significant differences among the information variables:
•
information needs (mean=3.75) are significantly greater than overall information
provision (mean=3.06) (t=6.048, p<.0001)
•
internal information needs (3.89) are significantly greater than internal information
provision (3.38) (t=4.06, p<.0001), and
•
external information needs (3.63) are significantly greater than external information
provision (2.73) (t=6.15, p<.0001).
Interestingly, Table IV shows that the judgmental memory variable has the greatest mean while
one would have expected procedural memory to be highest in this group of firms due to its over
reliance on rules and procedures and where the employees are routinely evaluated on their
compliance with these rules.
The correlations among the independent and the dependent variables are given in Table V.
Table V. Correlation Matrix among the Research Variables.
1 2 3 4 5 6 7 8 9 10
1 Procedural Memory -
2 Declarative Memory .23
-
3 Judgmental Memory
.35*
.01 -
4 Software Penetration
.48**
.02
.29* -
5 Storage Penetration .16 .02
.46** .41**
-
6 Network Penetration
.48**-.28*
.22 .24 .20
-
7 Communication Penetration .11 .17 .13
.50** .38*.30* -
8 Internal Information Needs -.15 .06 .02
-.26*
-.21 .23 .11
-
9 Internal Information Provision -.01 -.13 .04 .14 -.08
.29*.37 * .52 ***
-
10 External Information Provision
.27*
.06 .25 .18 .06 .14
.26 *
.16
.52 *** -
11 External Information Needs
a
.04 -.20 .16 .03 -.29 .14 -.08
.47 **
.38 * .34*
a
Adjusted for sign due to correction for skewness by transformation.
*
**
***
p <.05
p< .005
p< .0001
Interestingly, from among the three memory variables, only procedural memory and judgmental
memory correlate positively with each other (.35, p=.011). There are also significant correlations
between the memory variables and the technology variables ranging from .29 to .48. One can
notice the .28 (p=.036) negative correlation between declarative memory and network
penetration.
Only procedural memory correlates with the dependent information variable measuring external
information provision. However, as one would expect, IT correlates with several information
variables, either negatively with needs or positively with provision. for example, though not
associated with information provision, software penetration is negatively associated with
information needs (-.26, p=.046). both network and communication penetrations are associated
with internal information provision. The only variable other than procedural memory, correlating
11
with external information provision is communication penetration (.26, p=.044). No independent
variable correlates with external information needs.
The data of the correlation matrix raise two issues. First, most independent variables are
significantly inter-correlated suggesting multicollinearity might be present. Second, the
dependent variables demonstrate several significant inter-correlations. This is restrictive in the
sense that running multivariate tests would inflate the possibility of Type I error. Coupled with the
likely multicollinearity of the independent variables, the validity of the interpretation of the results
could become questionable.
To address the first issue, we used the orthogonal factor scores extracted from the principal
components analyses performed initially to extract an orthogonal set of component scores from
all the independent variables (Tabachnick and Fidell, 1989). This procedure allowed us to form
orthogonal variables which carry the same information as the original variables but which will not
correlate, thus reducing multicollinearity.
To avoid the implications of the second issue, we used multiple analysis of variance (MANOVA)
to analyze our data. It is inherent in the MANOVA procedure that tests on all univariate and
multivariate effects are performed on the dependent variables taken together and separately. To
perform these analyses, we split all the independent variables into two groups (low and high)
based on their median.
Results
Given the exploratory nature of this study, a series of MANOVAs was conducted investigating
main, multivariate and interaction effects between the independent variables and the information
dependent variables. No significant results involved the procedural memory and software
penetration variables. Furthermore, there were no main, multivariate, or interactive effects on the
external information needs dependent variable.
There were, however, main effects and interactive effects involving the other variables. Main and
interactive effects involved the storage, network, and communication variables as well as the
declarative and judgmental memory variables.
The main effect of storage penetration was on the internal information provision (F=9.30,
p=.004). Communication penetration had main effects on both the internal information needs
(F=5.05, p=.031) and the external information provision (F=4.62, p=.039) variables.
Four interactive effects were detected. The first was between storage penetration and
declarative memory on internal information needs (F=4.15, p=.050, see Figure 2). The second
between storage penetration and declarative memory on internal information provision (F=14.70,
p=.001, Figure 3). The third between storage penetration and declarative memory on external
information provision (F=8.46, p=0.006, Figure 4). And the fourth between network penetration
and judgmental memory on external information provision (F=5.20, p=.029, Figure 5).
The results thus clearly suggest that an interaction effect between memory and technological
variables on information needs and provision exist.
12
Low High
Storage Penetration
High Declarative Memory
Low Declarative Memory
F=4.15 (p=.050)
Low High
Storage Penetration
High Declarative Memory
Low Declarative Memory
F=14.70 (p=.001)
Figure 2. Interaction effect between
declarative memory and storage penetration
on the amount of internal information needs.
Figure 3. Interaction effect between
Declarative Memory and storage penetration
on the amount of internal information provision.
Low High
Storage Penetration
Low Declarative Memory
High Declarative Memory
F=8.46 (p=.006)
Low High
Network Penetration
High Judgmental Memory
Low Judgmental Memory
F=5.20 (p=.029)
Figure 4. Interaction effect between
Declarative Memory and storage penetration
on the amount of external information
provision.
Figure 5. Interaction effect between
judgmental memory and network penetration
on the amount of external information
provision.
We also note, from Figure 2, that, between low and high declarative memory, internal
information needs are high when there is not enough storage. This result is to be expected since
if technical, scientific, and administrative memories exist in the organization, but are not available
in electronic form because there is not sufficient storage, the needs for technical, scientific, and
administrative information will be augmented by the need to know where
to find it. On the other
hand, when both declarative memory and storage penetration are high, the need for internal
information is low, probably because storage is used to also store this kind of information.
The next two results (Figures 3 and 4) show interaction effects of declarative memory and
storage on both internal and external information provision. Both the nature and the form of
these interaction effects are unexpected. In fact, one would assume the interaction to be in favor
of increasing information provision when both storage and declarative memory are high. The
opposite is observed
8
.
Figure 5 shows that judgmental memory and network penetration interact significantly on the
amount of external information provision. Here, too, the same trend appears. In this case, it
would seem that external information provision is better when judgmental memory is high and
network penetration is low. This result goes counter to our expectations. Judgmental memory
8
The data showed the same pattern of relationships whether the Mahalanobis outliers are included (in the entire
sample) or not (in the reduced sample), except that the relationship shown in Figure 4 is no longer significant in the
reduced sample.
13
being more a matter of interpretation and experience, the fact that more technology is available
does not make it perceived as more useful since it seems that provision gets lower when
network penetration goes higher. But this would only explain one part of the results shown in
Figure 5, i.e., when both network penetration and judgmental memory are high. We could not
find any explanation for the provision being higher when network penetration is low and
judgmental memory is low than when they are both high.
Conclusion
The results of this study are somewhat unexpected. This is perhaps due to the lack of empirical
studies having tackled the measurement of organizational memory and the inclusion of both IT
and organizational memory in an integrated research model. This paper endeavored to
overcome this shortcoming by incorporating both IT and memory concepts into the information-
processing theory of the firm.
Unfortunately, most of our results do not support the view that IT and memory contribute
simultaneously to increase the provision of information in organizations. While assertions found
in the literature hypothesized that IT augments the benefits of organizational memory
(Ackerman, 1996; Lehner et al., 1998), this study could not confirm all of them. In fact, it would
seem as though IT and organizational memory have diverging effects on information provision.
These results are important because they highlight the effects that IT could have on learning in
general and on memory in particular. Because organizations expect that IT would augment
organizational memory, they would rely overly on it and expand less efforts in using other types
of memories. Could this result in a net negative effect on information availability and has such a
phenomenon been observed before?
We have already noted that IT-based and other memories differ in significant ways, one being
the additional search effort needed to retrieve information and knowledge when they are stored
electronically. Declarative memory, for example, has the characteristic of not being committed to
a particular use which could become a drawback as was already noted by cognitive
psychologists (Singley and Anderson, 1989) who note that “vast amounts of [declarative
memory] are potentially relevant in any problem-solving situation, and this leads to serious
problems of search” (p.220), a process by which stored information is recognized by its user as
relevant to a particular problem or goal (Wijnhoven, 1999). Search presumes knowledge about
what to search (the information), where to search it (in computers or elsewhere) and, in the case
of IT, how to search it (programs and query routines). With respect to computer-based
memories, this is in conformity with Tuomi’s (2000) notion of “reversed knowledge hierarchy”
whereby meaningful information emerges only when we have knowledge about it.
If such is the case, then the additional search effort entailed by computerized files and
databases would increase the difficulty of having access to the information needed. This would
increase the perception that information is less available since its access requires knowledge
that may be lacking. Users may find it difficult even to select from the available sources those
that are most appropriate given their needs (Lansdale, 1988). Or they may be unsure as to
whether knowledge documented in repositories is current or out-of-date (Galunic and Weeks,
1999).
When information is stored in computers, there always needs to be programs to help access it
and organizational members need to know how to use these programs. Furthermore,
organization members need tools to make sense out of the information found.
Another possible, and somewhat related, explanation could be found in both the psychological
expectations of computer users (see Lansdale, 1988) and the Computer Credibility literature
(Sheridan et al., 1983), which suggests that the trust that people put into computers may result in
poorer performance. For example, when typing a text, people are less careful because they rely
on the word-processor’s spell checker; they lose their arithmetic skills because they rely on
14
calculators, and their performance in using word-processor decreases when an intelligent agent,
an Advisor, consisting of a context-sensitive function, is turned on (Galletta et al., 2005).
Limitations of the Study
No study is perfect and this empirical investigation is no exception. The first limitation is the small
sample size which, coupled with the fact that all the work-units studied are affiliated to the same
group of companies, precludes us from generalizing our results to other organizations.
The fact that the data was collected via questionnaires constitutes another limitation, especially
that one of the advantages of questionnaires studies to tackle large samples has not been
realized.
The third limitation is related to the operationalization of the memory variables. Because this was
done for the first time and though the measures exhibited acceptable reliability, their content and
construct validity are still not established.
Suggestions for Future Research
This study opens avenues for future research to test the hypothesis that IT and organizational
memory have additive effects. This study failed to show this result. Other measures should
perhaps be used, especially in the case of organizational memory.
In Randall et al.’s (2001) study, there was a general preference among workers to ask a local
expert rather than interrogate manuals, computer screens, or other forms of knowledge support.
If even knowledge workers such as Andersen Consulting consultants more often ask their
colleagues for help to locate documents in the firm's repositories (Markus (2001) and if
engineers and scientists in search of assistance turn to colleagues five times more often than to
a computerized data base (Cross et al., 2001), future research should probably explore what
would people choose if they had the choice between IT and other means, and under what
conditions.
Is national culture involved? Knowledge and memory have often been the subject of
disagreements among researchers for whom knowledge is “a fundamentally cognitive concept”
and researchers who consider it as a “socially and culturally” derived phenomenon (Ackermann
and Halveson, 1998; Randall et al., 2001). More research is definitely needed studying
knowledge management in Arab countries perhaps through cross-comparisons with other
cultures.
In this paper, a distinction was made between IT-based memory and other types of memory.
Aside from IT and human memory, there might still be a lot of knowledge stored mainly in the
form of the organization and in the operation of the organization’s socio-technical system
(Lehner et al., 1998; Walsham and Barrett, 2005). Not all kinds of knowledge can be stored
electronically; some knowledge could be supported by IT and knowledge could be found in
control systems, such as standard procedures, rules and regulations, codes and codifications,
descriptions of work processes (Feldman and March, 1981). Future studies might consider
incorporating those aspects of organizational memory.
Clearly, the concepts related to organizational memory and their effects are yet to be discovered.
Future studies should address the issue of homogeneity of needs or use larger samples if
heterogeneity cannot be avoided. The issue of homogeneity has been addressed in several
studies (Miner, 1990; Tushman and Anderson, 1986) and is suspected to reduce the value and
effect of organizational memory. When organizational memory is heterogeneous, organizational
members would find it easier to access the information they need than to have to search it.
It may be premature to conclude that no matter the IT advances in a firm, it stills depends on its
overall environment. The fact that this study is one of the first to be performed in Tunisia, a
country that Henry (1998) describes as “information-shy” due to its seemingly peculiar approach
to information management, may be an incentive to explore the concepts related to information
and the way organizational memories are grasped in culturally different backgrounds and
environments.
15
[References available upon request from the first author]
