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Content uploaded by Murray E. Jennex
Author content
All content in this area was uploaded by Murray E. Jennex
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An Organizational Memory Information Systems Success Model: An
Extension of DeLone and McLean’s I/S Success Model
Murray Jennex
Edison International and University of Phoenix
jennexme@sce.com
Lorne Olfman, Pituma Panthawi, Yong-Tae Park
Claremont Graduate University
Lorne.Olfman, Pituma.Panthawi, Yong-
Tae.Park@cgu.edu
Abstract
This paper describes an organizational memory
information system (OMIS) Success Model that is based
on the I/S Success Model proposed by DeLone and
McLean [6]. The current model is refined from the
original through application of specific factors associated
with an OMIS. The paper briefly summarizes previous
research that explored effectiveness of OMIS, including a
case study of a station engineering unit at a nuclear power
plant, and shows that no quantitative study has been done
to test the effectiveness of OMIS for a cross-section of
organizations. It is proposed to test the OMIS Success
Model by surveying station engineering units at nuclear
power plants throughout the United States. These groups
do similar tasks, but will have different kinds of
organizational memory information systems. Measures for
the OMIS Success Model constructs that can be included
in the survey instrument are proposed. Other factors
affecting the possible outcomes of the study are discussed.
1. INTRODUCTION
The purpose of this paper is to develop a model for
measuring the effectiveness of organizational memory
information systems (OMIS). An OMIS is defined as “a
system that functions to provide a means by which
knowledge from the past is brought to bear on present
activities, thus resulting in increased levels of
effectiveness for the organization” ([17], p. 95). The
model presented here provides an explanation for why an
OMIS increases organizational effectiveness. In essence, it
allows measurement of a system that is thought to be an
OMIS. If the system in question increases organizational
effectiveness, then it would be considered an OMIS given
that it provides a means of bringing past knowledge to
bear on present activities.
It is unlikely that a direct causal relationship can be
shown between the presence of an OMIS and higher levels
of organizational effectiveness. DeLone and McLean [6]
showed that there is a multi-step process leading from the
quality of a system and its information to its impact on an
organization. Figure 1 contains their “I/S Success Model”.
Quality of a system and the information it produces affect
both use of the system and user satisfaction (which are
reciprocal constructs), which in turn produce an individual
impact, which produces an organizational impact. The
model presented in this paper specifies a similar block-
recursive model (cf. [4]) that is customized to the context
of a specific system, namely an OMIS.
The paper proceeds as follows. First, a definition of an
OMIS is presented, and justification for the development
of an OMIS Success Model is given. Next, the customized
model is outlined, and previous research that examines
OMIS effectiveness is presented. The paper then proposes
a field study to measure the OMIS model in the context of
maintenance of nuclear power plants. To conclude, some
of the problems in conducting such a study are discussed.
2. ORGANIZATIONAL MEMORY INFORMATION
SYSTEMS
Organizational memory has been defined by many
authors. There is no one agreed upon definition. Some
authors view it as abstract and supported by
concrete/physical memory aids such as databases (e.g.,
[19]). Others view it as concrete and including
computerized records and files (e.g., [8]). Stein and Zwass
[17] define it as “the means by which organizational
knowledge is transferred from the past to the present” (p.
90). In essence, they view an OMIS as a component of
organizational memory.
Stein and Zwass [17] present a framework for an OMIS
consisting of two layers. The first layer
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System Quality
Information
Quality
Use
User Satisfaction
Individual Impact
Organizational
Impact
Figure 1. DeLone and McLean’s [6] I/S success model
incorporates four subsystems that derive from four
effectiveness functions. These subsystems are described in
Table 1. The second layer consists of mnemonic functions
including knowledge acquisition, retention, maintenance,
search, and retrieval. These two layers can be either IT-
based or non-IT-based.
Table 1. OMIS effectiveness functions
(descriptions quoted from [17], p. 96)
Three forms of OMISs are possible: paper documents,
computer documents, and self-memory.
• Paper documents are organization-wide references
that reside in central repositories such as a
corporate library. Examples of paper documents
include reports, procedures, and technical
standards. An important part of this memory is in
the chronological histories of changes and revisions
to these paper documents as they reflect the
evolution of the organization’s culture and decision
making processes.
• Computer documents include all computer-based
information that is maintained at the work group
level or beyond. These may be made available
through downloads to individual workstations, or
may reside in central databases or file systems.
Additionally, there are the processes and protocols
built into the information systems that are reflected
in the interface between the system and the user, by
who has access to the data, and by the formats of
structured system inputs and outputs.
• Self-memory includes all paper and computer
documents that are maintained by an individual.
Typical components include files, notebooks,
written recollections, and other archives. These
typically do not have an official basis or format.
Each person’s self-memory is determined by what
is important to that person and reflects that
person’s experience with the organization.
It is expected that these forms of OMIS will have
overlapping information. This will be especially true for
IT-based components. Figure 2 illustrates the relationships
between these components.
Others' OMIS
Document
OMIS
Self-Memory
OMIS
Computer
OMIS
Figure 2. Components of an OMIS [10]
Effectiveness Function Description
Integration Coordination and
management of
information across the
organization.
Adaptation Ability of the organization
to adapt to changes in its
environment.
Goal Attainment Ability of the organization
to set goals and evaluate
the degree of their
fulfillment.
Pattern Maintenance Ability of the organization
to maintain the cohesion
and the morale of the work
force.
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Technical
Resources
Level of OMIS
Amount of OMIS
Use
Form of OMIS
Individual Impact
Organizational
Impact
User Satisfaction
with OMIS
Information
Quality
System Quality
Figure 3. OMIS success model
Stein and Zwass argue that certain “contingencies will
limit the implementation and use of an OMIS” (p. 107).
They note that even though an OMIS may be
demonstrated to be effective for an organization, the
project to develop it may not be initiated. Even if the
project is initiated, it may not be concluded. If the project
is concluded, the system may not be used. If the system is
used, it may not be used properly. And, even if used
properly, it may not achieve its full potential. A model of
OMIS success should enable the assessment of the extent
to which an implemented OMIS will achieve its potential
with respect to enhancing organizational effectiveness.
3. AN OMIS SUCCESS MODEL
The model developed in this paper follows from
DeLone and McLean’s [6] I/S Success Model. The
DeLone and McLean model is based on a review and
integration of 180 research studies that used some form of
system success as a dependent variable. It identifies six
system success constructs and shows how they are related
(see Figure 1). This paper adopts the generic framework of
the I/S Success Model, and customizes it to the context of
an organizational memory information system (see Figure
3). The model is a block-recursive one that includes 5
blocks. While the DeLone and McLean model implies that
system quality and information quality are part of one
block, the proposed model includes each as a separate
block. This is because the system quality block has been
expanded to include the characteristics of the OMIS.
3.1. System quality
The first block of the proposed model defines the
system quality in terms of the characteristics of the OMIS.
System quality describes how good the system is in terms
of its operational characteristics. For the proposed model,
the system quality block contains three constructs: the
technical capabilities of the organization, the form of the
OMIS, and the level of the OMIS. Technical resources
define the capability of an organization to develop and
maintain an organizational memory information system.
These include aspects such as amount of past experience
already gained in developing and maintaining an OMIS,
the amount of technical expertise that is used to develop
and maintain the OMIS, the type of hardware used to run
the OMIS, and the competence of the users.
Technical resources will impact both the level and form
of the OMIS. The level of the OMIS refers to its ability to
bring past information to bear upon current activities. The
form of OMIS refers to the extent to which it is
computerized and integrated. In addition, the form of the
OMIS should impact its level. Given the effectiveness of
information technology to provide timely information, it
its expected that a more fully computerized and integrated
system will provide a more sophisticated capability to
retrieve past information. This block shows that the level
of the OMIS is the final measurement of its capabilities in
terms of system quality, and can be used as a surrogate
measure of the block in terms of its effects on the system
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usage block.
3.2. Information quality
Information quality defines how good the system is in
terms of its output. Factors in this category span a broad
range from importance, relevance, usefulness and
informativeness to clarity, content, accuracy, and
completeness. Information quality affects the system usage
block.
3.3. Success measures in terms of usage
DeLone and McLean identified a reciprocal
relationship between two constructs related to system use.
Information use refers to the utilization of the outputs of
the system. This construct is most applicable as a success
measure when the use of a system is voluntary. User
satisfaction is a construct that measures perceptions of the
system by users. It is considered a good surrogate for
measuring system success when use of the system is
required, and therefore amount of use would be equal
regardless of the effectiveness of the system.
However, it is evident that both of these constructs
provide feedback to each other, especially where use is
voluntary. Use will influence user satisfaction either
positively or negatively, and user satisfaction will
influence use. A more satisfied user might be expected to
increase usage. This block leads to individual impact, and
therefore a combination of the two constructs can be used
as a surrogate measure of the block.
3.4. Individual and organizational impact
An individual’s use of a system will produce an impact
on that person’s performance in the workplace. In
addition, DeLone and McLean note that an individual:
‘impact’ could also be an indication that an
information system has given the user a better
understanding of the decision context, has
improved his or her decision-making productivity,
has produced a change in user activity, or has
changed the decision maker’s perception of the
importance or usefulness of the information system
(p. 69).
Each individual impact will in turn have an effect on the
performance of the whole organization. The DeLone and
McLean model views individual and organizational
impacts as separate constructs each forming their own
blocks. However, organizational impacts are typically not
the summation of individual impacts, so the association
between individual and organizational impacts is often
difficult to draw.
4. EVIDENCE FOR USING THE OMIS MODEL
The purpose of this section of the paper is to report on
previous studies that examined the effectiveness of
organizational memory information systems. Previous
research in organizational memory has mainly been aimed
at the definition of the construct, and the design of
organizational memory systems, and only a few empirical
studies have been published. None has reported a
quantitative study of the effectiveness of OMIS for a
cross-section of organizations.
Ackerman [1] studied six organizations which had
implemented his Answer Garden system. Answer Garden
[2] is a system designed to grow organizational memory in
the context of help-desk situations. Ackerman found that
only one organization had a successful implementation
because expectations of the capabilities of the system
exceeded the actual capabilities. Ackerman and Mandel
[3] found that a smaller task-based system was more
effective on the sub-organization level because of its
narrower expectations. They refer to this narrower system
as “memory in the small”.
Karsten [11] studied organizational memory in the
context of a small consulting firm. She found a
relationship between the form of the organization and the
roles that organizational memory played in each form.
Over a three-year period, under the control of three
managing directors, the organization changed from an
umbrella for private entrepreneurs to a hierarchy with a
well-defined structure to a network with collaborative
management. In each case, the common information space
[16], which is the means for facilitating collaboration,
changed to meet the needs of the organizational form. The
common information space represents a manifestation of
organizational memory. Karsten [11] did not set out to
study nor could she conclude whether it was the common
information space that led to effective organizational
functioning.
Sandoe and Olfman [15] reported a simulation study
that examined the effectiveness of three mnemonic forms
under varying conditions. Mnemonic forms represent
patterns or ways of remembering in organizations. One
form, structure-based remembering, which occurs through
formal and informal roles and rules, fits Cyert and
March’s [5] conception of memory as standard operation
procedures. A second form, relationship-based memory, is
retained in relationships and is characterized by mutuality,
trust, and esteem [12]. An example is informal
organizational networks. The third form, technology-based
remembering, occurs through symbolic and physical
artifacts such as books, databases, tools, and assembly
lines ([8], [19]). Sandoe and Olfman found that these
mnemonic forms performed differently depending on the
variability in both external and internal environments, and
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concluded that information technology has the potential to
buffer this variability.
Jennex [10] performed a detailed study of the
organizational memory information system used by the
station engineering unit of a nuclear power generating
station. This unit is charged with providing engineering
support to the production of electricity from the operation
of the nuclear plant. The support consists of:
• analyzing equipment and system problems
• designing and implementing problem solutions
• analyzing failures to determine root causes
• trending equipment and system performance to
ensure compliance with plant design bases
• performing safety and operability analyses
• ensuring the plant meets its regulatory activities.
Performance of these activities are critical to the safe
operation of the nuclear plant. The consequences of
workers making mistakes in this environment are more
economic than social since the plant has high levels of
safety features to protect the public from the release of
radioactivity. However, the economic consequences are
high in that errors could lead to large fines, increased
regulatory attention, or shutdown of the plant.
The station engineering unit consists of 56 cognizant
engineers, 25 support engineers, and 24 supervising
engineers (including managers) working in the areas of
mechanical, electrical, computer and controls engineering.
All members of the unit were asked to complete a
structured questionnaire with seventy-nine percent of the
staff (83 persons) providing responses. Twenty percent
(5 managers, 5 supervisors, and 11 cognizant and support
engineers), selected because of their knowledge of the
OMIS, participated in structured interviews.
The purpose of the Jennex study was to determine the
following: (1) the nature of the OMIS for the station
engineering unit; (2) the effectiveness of the OMIS in
terms of perceptions affecting usage and the competing
values model [14]; and (3) the extent to which the OMIS
impacted productivity at both individual and
organizational levels of analysis. It used quantitative and
qualitative analysis to study factors associated with the
generic I/S Success Model. Overall, the research found
that organizational effectiveness improved as the OMIS
effectiveness was enhanced. Additionally, the study
identified several measures that can be used to
operationalize the OMIS success model.
5. OPERATIONALIZATION OF THE SUCCESS
MODEL
Jennex [10] provided a basis for exploring a
quantitative analysis and test of the OMIS Success Model.
Table 2 illustrates how the various measures applied in the
study can be used to operationalize the factors of the
OMIS Success Model. In order to extend this work, it was
decided to develop a survey instrument to assess the
effectiveness of the OMIS of other nuclear power plant
station engineering organizations in the United States.
Since these organizations have similar characteristics and
goals, they provide an opportunity to gain a homogeneous
set of data to use for testing the model. The following
discussion outlines the measures to be used in the survey.
The mechanics for carrying out the survey have not been
finalized, but it is expected that the manager of each
station engineering organization will be contacted and
asked to distribute surveys to each of the engineers in the
organization. It is planned that a confirmatory factor
analytic technique will be used to statistically test the
model.
5.1. System quality
System quality was defined previously as how good the
system is in terms of its operational characteristics. Three
constructs were proposed for the system quality block and
to capture characteristics of the OMIS: the technical
capabilities of the organization, the form of the OMIS, and
the level of the OMIS.
Jennex found evidence to show that the capabilities of
the IS organization and the users can impact the success of
the OMIS. IS organization capabilities that enhanced
OMIS effectiveness included a fast, high capacity
infrastructure, strong application development skills,
network skills, and awareness of the user organization’s
OM requirements. Users’ capabilities that enhanced OMIS
effectiveness included a high degree of computer literacy
and high-end personal computers. Providing training on
how to ask questions and use memory was also found to
enhance OMIS effectiveness.
Given the importance of the above technical
capabilities as identified by Jennex, the goal will be to
measure the technical capabilities factor by focusing on
the overall experience of the development group in
building and maintaining networked systems that support
OM, the capabilities of the end-users of the OMIS, and the
level of hardware and operating system capabilities of
workstations.
Table 2. Jennex’s [10] findings applied to the OMIS success model
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The level of the OMIS was defined above as the ability
to bring past information to bear upon current activities.
This can be measured in terms of Stein & Zwass’s [17]
mnemonic functions including knowledge acquisition,
retention, maintenance, search, and retrieval. It is expected
that a more effective OMIS will include more
sophisticated levels of the these functions. For example, a
more sophisticated OMIS should contain the ability to do
filtering, guided exploration, and to grow memory [2].
The form of OMIS refers to the extent to which it is
computerized and integrated. In essence, the more
computerized the memory, the more integrated it can be.
That is, if all sources of the OMIS are available in
computer-based form, then it will be possible to more
effectively search and retrieve the OM. Integration also
speaks to the external consistency of the various forms of
OMIS. Jennex [10] found that although much of the OMIS
at the station engineering unit was computerized, there
were many different systems, each with varying kinds of
storage mechanisms and interfaces. These systems were
poorly integrated, relying mainly on the copy and paste
features of the Windows interface, and therefore limited
the ability of workers to utilize the OMIS effectively. It
was evident that more sophisticated technical resources
could produce a more integrated set of systems.
5.2. Information quality
Information quality was defined previously as how
good the system is in terms of its output. Measurement of
information quality is typically done from the perspective
of user perceptions, and is typically subjective. “Also,
these measures, while shown here as separate entities, are
often included as part of the measures of user satisfaction”
([6], pp. 65-66). Therefore, it is proposed to not
specifically measure information quality for the proposed
study, but rather to measure the information quality as part
of user satisfaction (see below).
5.3. Success measures in terms of usage
Information use refers to the utilization of the outputs
of the system. Igbaria, Pavri, and Huff [9] measured
information system usage on five dimensions: number of
tasks performed, actual daily usage, frequency of use (e.g.,
hourly, daily, etc.), number of application packages used,
and level of sophistication of usage. Jennex [10] measured
usage in a similar manner. He provided station engineering
employees with a list of OMIS components, then asked
them to indicate the number of times per day and the
Success Model Factor Data Collection Method Result
Technical Resources user competency survey users are computer literate but not experts
observation and document
research of IS support group
strong application development skills, network
skills
interview with IS support
Manager
awareness of need to support OM functions and
to provide OM infrastructure; not enough user
input
Form of OMIS survey of OM sources all forms supported
interview of OM sources all forms supported
Level of OMIS observation of OM use most past decision information could be readily
retrieved
interview on how used OM most information is quickly retrievable; rest is a
day or so
System Quality interview on overall OMIS fair to good -- needs more integration and better
infrastructure
Information Quality interview on how useful good -- almost too much information, some
timelines issues; quality depends on the diligence
of the person inputting
survey on near term job fit information perceived to be useful
Amount of OMIS use survey on usage all forms used with computer and self-memory
forms used most
User Satisfaction survey on perceived benefit supported continued voluntary use of the OMIS
Individual Impact interview on productivity OMIS use considered a basic skill that can
improve job performance
Organizational Impact document research improved external ratings; improved capacity
factors; less unscheduled downtime
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minutes per access for each component, the frequency of
use (as above), and to give an estimate of the percentage
of persons in the user’s work group that used that
component. This format should provide a reasonable
measurement of OMIS usage.
In addition to current use of information, the success
model should also be concerned with the potential future
use of information. Jennex used Thompson, Higgins, and
Howell's [18] Perceived Benefit Model to predict
continued voluntary usage of the OMIS for the station
engineering organization. He included questions in his
survey that comprised four factors adapted from
Thompson et al's perceived benefit measure:
• Job fit of OM, near term consequences of using the
OMIS
• Job fit of OM, long term consequences of using the
OMIS
• Social factors in support of using the OMIS
• Complexity of the OMIS.
The near term job fit factor additionally provides a
measure of information quality as it measures the
perceived job benefit of the OMIS. The other factors
ensure that the environment is conducive to continued
OMIS usage. A subset of questions from the perceived
benefit model will be used in the proposed survey.
User satisfaction is a construct that measures
perceptions of the system by users. This is one of the most
frequently measured aspects of I/S Success, and it is also a
construct with a multitude of measurement instruments [6].
User satisfaction can relate to both product and service. As
noted above, product satisfaction is often used to measure
information quality. The proposed study will measure both
product and service satisfaction. Product satisfaction will
be measured using the 12-item instrument developed by
Doll and Tordzadeh [7]. This measure addresses
satisfaction with content, accuracy, format, ease of use,
and timeliness. Service satisfaction will be measured using
a subset of the instrument developed by Pitt, Watson, and
Kavan [13].
5.4. Individual impact
The impact of an OMIS on an individual is rooted in
performance changes, but has other facets. For the
purposes of the OMIS Success Model, the individual
impact will be measured in terms of productivity. Jennex
queried supervisors and managers to determine what they
believed was the nature of individual productivity in the
context of the station engineering unit. The interviews
revealed a complex set of factors that includes:
• timeliness in completing assignments and doing them
right the first time
• number of assignments completed
• identification and completion of high priority
assignments
• completeness of solutions
• quality of solutions (thoroughness and accuracy)
• complexity of the work that can be assigned to an
engineer
• client satisfaction.
Despite the complexity and detail of this set of factors,
Jennex found that it is very difficult if not impossible to
determine quantitatively the productivity of a particular
engineer. It can be noted that Jennex also asked 20
engineers to indicate whether they were more productive
now than 5 or 10 years ago, and all but one thought they
were. The proposed study will include self-assessment
productivity measures based on the above noted factors.
All subjects in the proposed study will be doing similar
jobs to those in the Jennex research.
5.5. Organizational impact
Organizational impacts relate to the effectiveness of the
organization as a whole. For a nuclear power plant,
specific measures of effectiveness are available. These
measures relate to assessments performed by external
organizations, as well as those performed internally.
External assessments can be found for each nuclear plant,
so it is possible to compare them in terms of overall
performance, which is given as a categorization rating.
However, these are very broad measures, and the extent to
which these are capable of measuring OMIS success is
questionable .
Jennex [10] found organization-specific measures that
could be used to more directly assess the effectiveness of
the OMIS. Two measures: “unit capability”, which is the
ability of the station engineering unit to evaluate and
correct problems; and, “unplanned scrams”, which is the
ability to evaluate and solve problems, were identified. It
is expected that these data are available on a consistent
basis across station engineering units at various nuclear
plants.
Assessment of OMIS effectiveness using the competing
values model was suggested by Stein and Zwass [17]. As
noted earlier in this paper, this model includes four
components: integration, adaptation, goal attainment, and
pattern maintenance. A set of perceptual measures for
these components was developed by Quinn and
Rohrbaugh [14]. Jennex did not specifically use these
measures, but instead conducted interviews, and analyzed
systems and documents. He concluded that the OMIS was
effective in terms of achieving the goals of the four
functions. It is proposed to include the Quinn and
Rohrbaugh [14] instrument in the survey to capture
perceptions of OMIS effectiveness in terms of
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organizational impact.
6. DISCUSSION AND CONCLUSION
One of the most difficult aspects of the measurement
process is to clearly define the nature of the OMIS in
terms of its components. These components will not be
consistent across each of the organizations to be surveyed.
Jennex [10] did extensive research to identify all of the
computer-based and document-based components of the
OMIS in question. His approach was to identify potential
components of the OMIS, then ask the engineers to rate
the extent to which each of these was utilized for OMIS
functions. It will likely be required to ask each station
engineering unit manager to compile a list of components
prior to finalizing the survey each particular organization.
In this way, OMISs should be able to be compared in
terms of level.
Another critical aspect of survey research of the form
proposed here is the length of the instrument. Length will
be a factor in the rate of return of the survey, but testing
the full OMIS Success Model will require a lengthy
instrument. It will be imperative to enlist station
engineering unit managers who are supportive of this
research (as also noted above). The survey distributed by
Jennex had a return rate of about 80%, but he was on-site.
There are approximately 50 nuclear power plants that
could be surveyed, and the average number of engineers of
station engineering units is about 80 persons. Assuming
20% (about 10) of the station engineering units can be
counted on to assist in the survey process, and assuming
the return rate at a particular site would be in the order of
25%, this would yield 200 returned surveys, which should
be enough to provide the necessary power to test the
proposed model.
The current body of research on organizational memory
information systems has been aimed at defining the
concept of organizational memory, at showing how this
concept can be applied in an information systems context,
and to a lesser extent at providing some empirical
evidence from case studies that OMIS are effective. This
paper defines a model for assessing the effectiveness of an
organizational memory information system, and a
quantitative field study to test the model. The model is
based on the I/S Success Model proposed by DeLone and
McLean [6], and extends it by examining previous
research in organizational memory systems, and through
the findings of a case study [10] of the organizational
memory information systems of the station engineering
group at a nuclear power plant. Not only will the survey
results be used to refine the model, but they will also
enable a comparison of the effectiveness of various kinds
of OMIS.
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