The Concept of Information Overload: A Review of Literature From Organization Science, Accounting, Marketing, MIS, and Related Disciplines

Abstract

Based on literature from the domains of organization science, marketing, accounting, and management information systems, this review article examines the theoretical basis of the information overload discourse and presents an overview of the main definitions, situations, causes, effects, and countermeasures. It analyzes the contributions from the last 30 years to consolidate the existing research in a conceptual framework and to identify future research directions.

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The Concept of Information Overload: A Review of Literature from Organization
Science, Accounting, Marketing, MIS, and Related Disciplines
Martin J. Eppler a; Jeanne Mengis a
a Institute of Corporate Communication, University of Lugano, Lugano, Switzerland
Online Publication Date: 01 November 2004
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The Information Society, 20: 325–344, 2004
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ISSN: 0197-2243 print / 1087-6537 online
DOI: 10.1080/01972240490507974
The Concept of Information Overload: A Review
of Literature from Organization Science, Accounting,
Marketing, MIS, and Related Disciplines
Martin J. Eppler and Jeanne Mengis
Institute of Corporate Communication, University of Lugano, Lugano, Switzerland
Based on literature from the domains of organization science,
marketing, accounting, and management information systems, this
review article examines the theoretical basis of the information
overload discourse and presents an overview of the main defini-
tions, situations, causes, effects, and countermeasures. It analyzes
the contributions from the last 30 years to consolidate the existing
research in a conceptual framework and to identify future research
directions.
Keywords information explosion, information management strate-
gies, information overload, information processing,
information skills, information technology
In this article, we present a review of the literature on in-
formation overload in management-related academic pub-
lications. The main elements of our approach are literature
synopsis, analysis, and discussion (Webster & Watson,
2002). These three elements serve, in our view, the three
main purposes of a literature review, namely, to provide an
overview of a discourse domain (e.g., compiling the main
terms, elements, constructs, approaches and authors), to
analyze and compare the various contributions (as well as
their impact), and to highlight current research deficits and
future research directions. These three objectives should
be met, with regard to the topic of information overload,
as a clear overview, an analysis of the major contribu-
tions, and an identification of future research needs still
missing for this topic. The literature review should also
Received 27 October 2002; accepted 20 May 2004.
We thank the four anonymous reviewers and the two editors for their
insightful suggestions.
Address correspondence to Martin J. Eppler, Institute of Corporate
Communication, University of Lugano, Via G. Buffi, 13, 6900 Lugano,
Switzerland. E-mail: Martin.Eppler@lu.unisi.ch
help readers (researchers and managers alike) to recognize
information overload symptoms, causes, and possible
countermeasures in their own work environment, as the
flood of potentially relevant information has become a
ubiquitous research and business problem, from reading
relevant articles or reports, to screening e-mails or brows-
ing the Internet.
While this is not the first review article on the topic
of information overload (see Edmunds & Morris, 2000),
it is the first one to analyze the problem of information
overload across various management disciplines, such as
organization science, accounting, marketing, and manage-
ment information systems (MIS). Other review articles on
the subject follow a discipline-based approach. Malhotra
et al. (1982) and more recently Owen (1992) focus on con-
sumer research (see also Meyer, 1998); Schick et al. (1990)
examine relevant accounting literature; and Edmunds and
Morris (2000), Grise and Gallupe (1999/2000), and Nelson
(2001) concentrate on MIS research. Our review of con-
tributions in the area of information overload is interdis-
ciplinary because it aims to identify similarities and dif-
ferences among the various management perspectives and
show to what extent they have discussed information over-
load. We hope that by doing so, we can identify syner-
gies between the different streams of information over-
load research and highlight future research areas. Another
benefit of an interdisciplinary literature review is that it
can provide a more (cross-)-validated and general col-
lection of possible symptoms, causes, and countermea-
sures and thus lead to a more complete understanding of
the phenomenon. This literature-based understanding can
then be used to construct testable models on information
overload.
A second difference of our review in relation to prior
contributions is the way that the literature is summarized
and analyzed, as we present the results of our review
in a highly compressed and often visual format.Byour
providing various diagrammatic overviews of the reviewed
325
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326 M. J. EPPLER ET AL.
literature, patterns in the development of the field can be-
come visible. The major benefit of this visual approach
is a more concise representation of the discourse domain,
which allows for easier comparisons and hopefully also
leads to a reduction of information overload for our
readers.
THE CONCEPT OF INFORMATION OVERLOAD
In ordinary language, the term “information overload”
is often used to convey the simple notion of receiving
too much information. Within the research community,
this everyday use of the term has led to various con-
structs, synonyms, and related terms, such as cognitive
overload (Vollmann, 1991), sensory overload (Libowski,
1975), communication overload (Meier, 1963), knowledge
overload (Hunt & Newman, 1997), and information fa-
tigue syndrome (Wurman, 2001). These constructs have
been applied to a variety of situations, ranging from au-
diting (Simnet, 1996), to strategizing (Sparrow, 1999),
business consulting (Hansen & Haas, 2001), management
meetings (Grise & Gallupe, 1999/2000), and supermarket
shopping (Jacoby et al., 1974; Friedmann, 1977), to name
butafew overload contexts (for an extended list of
the contexts in which information overload has been dis-
cussed in management-related academic literature see
Table 1).
Research on information overload relevant for the realm
of management has mainly been undertaken in the areas
of accounting (e.g., Schick et al., 1990), management in-
formation systems (MIS) (initially highlighted by Ackoff,
1967), organization science (e.g., Galbraith, 1974;
Tushman & Nadler, 1978), and marketing and more spe-
cially consumer research (e.g., Jacoby, 1984; Keller &
Staelin; 1987; Malhotra, 1984). The main focus of these
disciplines is how the performance (in terms of adequate
decision making) of an individual varies with the amount
of information he or she is exposed to. Researchers across
various disciplines have found that the performance (i.e.,
the quality of decisions or reasoning in general) of an indi-
vidual correlates positively with the amount of information
he or she receives—up to a certain point. If further infor-
mation is provided beyond this point, the performance of
the individual will rapidly decline (Chewning & Harrell,
1990). The information provided beyond this point will no
longer be integrated into the decision-making process and
information overload will be the result (O’Reilly, 1980).
The burden of a heavy information load will confuse the in-
dividual, affect his or her ability to set priorities, and make
prior information harder to recall (Schick et al., 1990).
Figure 1 provides a schematic version of this discovery. It
is generally referred to as the inverted U-curve, following
the initial work of Schroder Driver, and Streufert (Schroder
et al., 1967).
FIG. 1. Information overload as the inverted U-curve.
This inverted U-curve represents the first important def-
inition of information overload, which was strongly de-
bated in the following (see Malhotra et al., 1982; Russo,
1974; or McKinnon & Bruns, 1992). For an overview of the
various ways researchers have marked the point at which
information overload occurs, see Table 2.
Authors in the field of marketing define information
overload by comparing the volume of information supply
(e.g., the number of available brands) with the information-
processing capacity of an individual. Information over-
load occurs when the supply exceeds the capacity. Dys-
functional consequences (such as stress or anxiety) and
a diminished decision quality are the result. A similar
wayofconceiving the information overload phenomenon
compares the individual’s information-processing capac-
ity (i.e., the quantity of information one can integrate into
the decision-making process within a specific time pe-
riod) with the information-processing requirements (i.e.,
the amount of information one has to integrate in order
to complete a task). This is the “classic” definition of in-
formation overload, based on the information-processing
view of the organization suggested by Galbraith (1974) and
expanded by Tushman and Nadler (1978). Following their
reasoning, information overload can be explained via the
following formula: information processing requirements
>information processing capacities. The terms “require-
ments” and “capacities” in this definition can be measured
in terms of available time. The requirements refer to a given
amount of information that has to be processed within a
certain time period. If the capacity of an individual only
allows a smaller amount of information to be processed
in the available time slot, then information overload is
the consequence. Tushman and Nadler define informa-
tion processing in this context as the “gathering, inter-
preting, and synthesis of information in the context of or-
ganizational decision making” (Tushman & Nadler, 1978,
p. 614). Many variations of this definition exist. Schick
et al. (1990) also stress the time factor as the most
important issue regarding the information overload prob-
lem. Interestingly, this discussion includes the Schroder
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THE CONCEPT OF INFORMATION OVERLOAD: REVIEW 327
TABLE 1
Information overload situations
Context/overload situation References
Information retrieval, organization, •Searching on the Internet Berghel, 1997
and analysis processes •Screening medical information Bawden, 2001
•Financial distress analysis Chewning and Harrell, 1990
•Evaluating the variety of product
functions
Herbig and Kramer, 1994
•Analysis activities (strategic
portfolio, environmental, new
product analysis, service decisions)
Meyer, 1998
•Investment analysis Tuttle and Burton, 1999
•Library management Meier, 1963
Decision processes •Managerial decisions in general Ackoff, 1967; Iselin, 1993
•Management (project, strategic,
production management)
Chervany and Dickson, 1974; Haksever and
Fisher, 1996; Meyer, 1998; Sparrow, 1999
•Supermarkets (choice of product) Friedmann, 1977; Jacoby et al., 1974
•Bankruptcy prediction process Casey, 1980; Iselin, 1993
•Capital budgeting process Swain and Haka, 2000
•Welfare assistance (decisions about
type and amount)
O’Reilly, 1980
•Innovation choice Herbig and Kramer, 1994
•Price setting Meyer, 1998
•Advertising media selection Meyer, 1998
•Strategy development Sparrow, 1999
•Physician’s decision making Hunt and Newman, 1997
•Financial decision making Iselin, 1988; Revsine, 1970
•Brand choice (consumer decision
making)
Jacoby et al., 1974, 1987; Malhotra, 1982;
Owen, 1992; Scammon, 1977; Wilkie, 1974
•Aviation O’Reilly, 1980
Communication processes •Meetings Schick et al., 1990
•Telephone conversations Schick et al., 1990
•The use of groupware applications Schultze and Vandenbosch 1998
•Bulletin board systems (BBS) Hiltz and Turoff, 1985
•Face-to-face discussions Sparrow, 1999
•Telephone-company services Griffeth et al., 1988
•Electronic meetings Grise and Gallupe, 1999, 2000
•Idea organization Grise and Gallupe, 1999, 2000
•E-mail Bawden, 2001; Speier et al., 1999; Denning,
1982
•Management consulting Hansen and Haas, 2001
•City interactions Milgram, 1970
•Disclosure law, contract complexity,
legal disclaimers
Grether et al., 1986
et al. (1967) view that information load and processing
capacity are not independent, since the former can influ-
ence the latter—that is, high information load can increase
one’s processing capacity up to a certain point (see also
Schultze & Vandenbosch, 1998). In other studies (Iselin,
1993; Keller & Staelin, 1987; Owen, 1992; Schneider,
1987), not only the amount of information and the avail-
able processing time (i.e., the quantitative dimension),
but also the characteristics of information (i.e., the qual-
itative dimension) are seen as major overload elements.
Keller and Staelin refer to the overall quality or “useful-
ness of the available ...information” (1987, p. 202), while
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328 M. J. EPPLER ET AL.
TABLE 2
Definitions of information overload
Definitions Components/dimensions References
The decision maker is considered to have
experienced information overload at the point
where the amount of information actually
integrated into the decision begins to decline.
Beyond this point, the individual’s decisions
reflect a lesser utilization of the available
information.
•Inverted U-curve: relationship between
amount of information provided and
amount of information integrated by
decision maker
•Information utilization
Chewning and Harrell (1990),
Cook (1993), Griffeth et al.
(1988), Schroder et al.
(1967),
Swain and Haka (2000)
Information overload occurs when the volume of
the information supply exceeds the limited
human information processing capacity.
Dysfunctional effects such as stress and
confusion are the result.
•Volume of information supply
(information items versus - chunks)
•Information processing capacity
•Dysfunctional consequences
Jacoby et al. (1974),
Malhotra (1982),
Meyer (1998)
Information overload occurs when the
information-processing requirements
(information needed to complete a task) exceed
the information-processing capacity (the
quantity of information one can integrate into the
decision-making process).
•Information-processing capacity
•Information-processing requirements
Galbraith (1974),
Tushman and Nadler (1978)
Information overload occurs when the
information-processing demands on time to
perform interactions and internal calculations
exceed the supply or capacity of time available
for such processing.
•Time demands of information processing;
available time versus invested time
•Number of interactions (with
subordinates, colleagues, superiors)
•Internal calculations (i.e., thinking time)
Schick, et al. (1990),
Tuttle and Burton (1999)
Information overload occurs when the
information-processing requirements exceed the
information-processing capacity. Not only is the
amount of information (quantitative aspect) that
has to be integrated crucial but also the
characteristics (qualitative aspect) of
information.
•Information-processing requirements
•Information-processing capacity
•Quantitative and qualitative dimensions of
information (multidimensional approach)
Keller and Staelin (1987),
Schneider (1987),
Owen (1992), Iselin (1993)
Information overload occurs when the decision
maker estimates he or she has to handle more
information than he or she can efficiently use.
•Subjective component: opinion, job and
communication satisfaction
•Situational factors and personal factors
Abdel-Khalik (1973), Iselin
(1993), O’Reilly (1980),
Haksever and Fisher (1996)
Amount of reading matter ingested exceeds
amount of energy available for digestion; the
surplus accumulates and is converted by stress
and overstimulation into the unhealthy state
known as information overload anxiety.
•Subjective cause component: energy
•Symptom: stress, overstimulation
•Subjective effect: information overload
anxiety
Wurman (1990), Wurman
(2001), Shenk (1997)
Schneider (1987) distinguishes various information attri-
butes, such as the level of novelty, ambiguity, uncertainty,
intensity, or complexity. These information characteristics
or quality attributes can either contribute to overload or
reduce it.
Beyond these approaches that try to conceptualize and
measure the phenomenon of overload objectively, there
are others that conceive overload on the basis of sub-
jective experience. Authors who have followed this ap-
proach are O’Reilly (1980), Haksever and Fisher (1996),
and Lesca and Lesca (1995). In this “subjective” view
of overload, the feelings of stress, confusion, pressure,
anxiety, and low motivation are the crucial factors that
signal the occurrence of information overload. Empiri-
cal research that follows this subjective view of the over-
load phenomenon typically employs interviews or survey
methods (such as Haksever & Fisher, 1996) as opposed to
experiments.
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THE CONCEPT OF INFORMATION OVERLOAD: REVIEW 329
This brief overview of the most frequently used defini-
tions and the contexts within which they were developed
delineates the intellectual territory which is examined in
this literature review. Having described the background of
the overload concept, we next briefly outline the method-
ology used to analyze the relevant literature.
METHODOLOGY
To screen the relevant articles within the literature on infor-
mation overload, we used the electronic database provided
by EBSCOhost and limited our research to the articles
included by the Business Premier Source. This database
provides full-text access to 3000 journals, of which more
than 1000 are peer reviewed. EBSCOhost enabled us to
search in the title or abstract of an article with the fol-
lowing keywords: information overload, information load,
cognitive overload, and cognitive load, which resulted in
a total number of 548 retrieved articles. In order to reduce
this large number to a more relevant subset, we introduced
further criteria (see Figure 2), which were: first, a publi-
cation date after 1970 (when computers started to be used
more extensively in the workplace); second, that the ar-
ticle is peer reviewed (which resulted in 205 remaining
articles); third, that information overload is a dominant
and systematically addressed subject in the article and not
just mentioned once or twice (resulting in a total of 168
articles); and finally, that the article approaches the sub-
ject within the context of one of the four areas of interest,
namely, accounting, marketing, MIS, and organization sci-
ence (with regard to the article’s topics and its publication
journal). This selection procedure has led to a total num-
FIG. 2. Selection criteria and article base.
ber of 97 considered articles. The 71 articles that were
eliminated discussed information overload in very specific
contexts that are quite different from those of today’s orga-
nizations. They discussed information overload in contexts
such as library and bibliographic research, documentation
of large-scale engineering designs, and students conduct-
ing research for their essays). Figure 2 reveals that the
greatest number of retained articles comes from the mar-
keting domain, followed by articles within organization
science, then accounting, and finally MIS had the smallest
number of articles on the subject.
One limitation of this methodology is that some arti-
cles that have dealt with the issue, but have used labels
other than the four terms we used as keywords, are not
taken into consideration (i.e., labels such as data smog,
information fatigue/overkill/overabundance/breakdown/
explosion/deluge/flood/stress/plethora, document tsun-
ami, sensory overload, etc.; see Eppler, 1998, for these
and other labels). These different terms, however, have
not achieved wide acceptance within the scientific com-
munity and hence do not represent core contributions to
this scientific debate. Another limitation of our approach
is that contributions on information overload that discuss
the phenomenon from other perspectives (such as psy-
chology, health care, and mass communication) are not
extensively addressed. Examples of such important contri-
butions include Miller’s “The magical number seven plus
or minus two” (Miller, 1956) and Simon’s seminal “Infor-
mation processing models of cognition” (Simon, 1979), to
name but two crucial contributions. In order to moderate
this limitation, we used an additional inclusion criterion:
If a publication was cited in more than two other overload
articles, we screened it to see whether information over-
load was indeed a major topic of the publication, and if
that was the case, we included it in our analysis. We pro-
ceeded likewise for books that have been cited frequently
in relevant journal articles (such as Wurman, 1990, 2001;
Shenk, 1997).
A CONCEPTUAL FRAMEWORK FOR
INFORMATION OVERLOAD RESEARCH
In order to provide a more complete (and less fragmented)
picture of the research conducted on information over-
load, the following framework lays out the most impor-
tant topic clusters in the literature and underscores their
relationships. These topic clusters are the main causes
of information overload, the symptoms, and appropriate
countermeasures for mitigating the problem.
It is important to note that the framework depicted
in Figure 3 is not based on a linear logic of causes and ef-
fects, but instead emphasizes a system of circular,
interdependent relationships. Correspondingly, it stresses
the fact that any countermeasure that is aimed at a specific
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330 M. J. EPPLER ET AL.
FIG. 3. A conceptual framework to structure research on information overload.
overload cause can have significant side effects on other
causes. Although this fact is frequently acknowledged in
literature (e.g., Bawden, 2001), it has scarcely been ex-
plored empirically (for an exception, see Evaristo, 1993).
In particular, the effect of certain (new) information tech-
nology applications on the quality of information (see
Wang et al., 1998), on the motivation of the individual,
and on task parameters has been neglected. Also, a con-
certed effort needs to be made to employ research meth-
ods that can capture contextual factors (such as industry
characteristics, the firm’s development stage, and the staff
structure) that are of critical importance for the occurrence
of overload. In general, research that provides “deep con-
text” is missing, as most information overload research is
experimental, survey based, or purely conceptual.
This framework also highlights the fact that there can-
not be a definitive solution for information overload. There
will always be a need for a continuous cycle of improve-
ment and refinement. We discuss the main elements (the
causes, symptoms and countermeasures) of the framework
and the relevant literature in the subsequent sections. At the
end of this section, we also demonstrate how this concep-
tual framework can be converted into empirically testable
models.
Causes of Information Overload
The main reasons for information overload at organiza-
tional and interpersonal levels can be related to five con-
structs, as shown in Figure 3. These inductively generated
constructs are the information itself (its quantity, frequ-
ency, intensity, and quality), the person receiving, pro-
cessing, or communicating information, the tasks or pro-
cesses that need to be completed by a person, team, or
organization, the organizational design (i.e., the formal
and informal work structures), and the information tech-
nology that is used (and how it is used) in a company.
Usually information overload emerges not because of one
of these factors but because of a mix of all five causes.
All five causes influence the two fundamental variables of
information overload: the information processing capac-
ity (IPC)—which is for example influenced by personal
characteristics—and the information processing require-
ments (IPR)—which are often determined by the nature of
the task or process. We discuss these five causes and their
influence on IPC and IPR briefly in the next paragraphs.
An important factor influencing the occurrence of
information overload is the organizational design of
a company (Galbraith, 1974; Tushman & Nadler, 1978).
Changes in the organizational design, for instance, due to
disintermediation or centralization (Schneider, 1987) or
because of a move to interdisciplinary teams (Bawden,
2001), can lead to greater IPRs because they create the
need for more intensive communication and coordination.
On the other hand, better coordination through standards,
common procedures, rules, or dedicated coordination cen-
ters (Galbraith, 1974) can reduce the IPR and positively
influence the IPC (Galbraith, 1974; Schick et al., 1990;
Tushman & Nadler, 1978; for other organizational
design elements that influence information overload see
Schneider, 1987).
After organizational design, the next important factor is
the nature of information itself. Schneider (1987) stresses
the fact that it is not only the amount of information that
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THE CONCEPT OF INFORMATION OVERLOAD: REVIEW 331
determines information overload, but also the specific
characteristics of information (also see Sparrow, 1998).
Such characteristics are the level of uncertainty associ-
ated with information and the level of ambiguity, novelty,
complexity, and intensity (Schneider, 1987). Simpson and
Prusak (1995) argue that modifying the quality of infor-
mation can have great effects on the likelihood of infor-
mation overload. Improving the quality (e.g., conciseness,
consistency, comprehensibility, etc.) of information can
improve the information-processing capacity of the indi-
vidual, as he or she is able to use high-quality informa-
tion more quickly and better than ill-structured, unclear
information.
The person and his or her attitude, qualification, and ex-
perience are another important factor. While earlier studies
simply state that a person’s capacity to process information
is limited (Jacoby et al., 1974; Galbraith, 1974; Malhotra,
1982; Simon, 1979; Tushman & Nadler, 1978), more re-
cent studies include specific limiting factors such as per-
sonal skills (Owen, 1992), the level of experience (Swain
& Haka, 2000), and the motivation of a person (Muller,
1984). Personal traits thus directly affect IPC.
Another important factor is the tasks and processes that
need to be completed with the help of information. The
less a process is based on reoccurring routines (Tushman
& Nadler, 1975) and the more complex it is in terms of the
configuration of its steps (Bawden, 2001; Grise & Gallupe,
1999, 2000), the higher is the information load and the
greater is the time pressure on the individual (Schick et al.,
1990). The combination of these two factors that increase
the IPR can lead to information overload. Information
overload is especially likely if the process is frequently in-
terrupted and the concentration of the individual suffers as
a consequence (Speier et al., 1999). Information overload
is also more likely if managers face an ever greater num-
ber of parallel projects or tasks that they have to manage
(see Wurman, 2001). In this way, complex tasks or pro-
cesses directly increase the IPR. This fact is aggravated by
a reduced IPC as a result of frequent context switching or
distraction.
Finally, information technology and its use and misuse
are a major reason why information overload has become
a critical issue in many organizations in the 1980s and
1990s. The development and deployment of new infor-
mation and communication technologies, such as the In-
ternet, intranets, and extranets, but especially e-mail, are
universally seen as one major cause of information over-
load (Bawden, 2001). There are, however, also arguments
in favor of e-mail. Edmunds and Morris (2000), for ex-
ample, stress advantages like the fact that e-mail is an
asynchronous form of communication and is less likely to
interrupt the normal work flow. Closely related to the prob-
lem of e-mail overload is the discussion of pull versus push
technologies and whether they have a positive or negative
impact on an individual’s IPC and IPR. Pushing selected
pieces of information to specific groups reduces on the
one hand their information retrieval time, but increases
on the other the amount of potentially useless information
that a person has to deal with (Edmunds & Morris, 2000).
In addition, it causes more frequent interruptions (Speier
et al., 1999). Information technology can thus potentially
increase the individual’s IPC while at the same time in-
creasing the IPR.
A complete list of the specific overload causes that are
mentioned in the relevant literature can be found in Table 3.
It is structured according to the five categories discussed
earlier.
Having reviewed the major causes of information over-
load and their impact on IPC and IPR, we can now look at
their effects or observable symptoms.
Symptoms of Information Overload
One of the first researchers to examine the effects of over-
load was the American psychologist Stanley Milgram
(1970), who analyzed signal overload for people living
in large cities. In his study, he identified six common reac-
tions to the constant exposure to heavy information load,
which are allocation of less time to each input, disregard
of low-priority inputs, redrawing of boundaries in some
social transactions to shift the burden of overload to the
other party of the exchange, reduction of inputs by filtering
devices, refusal of communication reception (via unlisted
telephone numbers, unfriendly facial expressions, etc.),
and finally creation of specialized institutions to absorb
inputs that would otherwise swamp the individual (see
also Weick, 1970, for this point).
In the organizational context, frequently described
symptoms of information overload on the individual level
are a general lack of perspective (Schick et al., 1990),
cognitive strain and stress (Malhotra, 1982; Schick et al.,
1990), a greater tolerance of error (Sparrow, 1999), lower
job satisfaction (Jacoby, 1984), and the inability to use
information to make a decision (Bawden, 2001)—the so-
called paralysis by analysis. Many other symptoms noted
by different researchers are listed in Table 4.
The big question with regard to effects of information
overload is whether and how it impacts decision accuracy,
decision time, and general performance. While research re-
sults have often been contradictory, especially among the
groundbreaking studies in marketing (the inconsistencies
were in part due to methodological problems; see Jacoby
et al., 1974; Malhotra et al., 1982; Muller, 1984), there is
wide consensus today that heavy information load can af-
fect the performance of an individual negatively (whether
measured in terms of accuracy or speed). When infor-
mation supply exceeds the information-processing capac-
ity, a person has difficulties in identifying the relevant
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332 M. J. EPPLER ET AL.
TABLE 3
Causes of information overload
Causes of information overload References
Personal factors •Limitations in the individual human
information-processing capacity
Herbig and Kramer, 1994
•Decision scope and resulting documentation needs Kock, 2001
•Motivation, attitude, satisfaction Muller, 1984
•Personal traits (experience, skills, ideology, age) Owen, 1992; Hiltz and Turoff, 1985;
Muller, 1984; Schneider, 1987; Swain
and Haka, 2000
•Personal situation (time of the day, noise, temperature,
amount of sleep)
Owen, 1992; O’Reilly, 1980
•Senders screen outgoing information insufficiently Van Zandt, 2001
•Users of computers adapt their way of interacting with
computers too slowly with respect to the technological
development
Maes, 1994
•Social communication barriers break down Schultze and Vandenbosch, 1998
Information characteristics •Number of items of information rises Bawden, 2001; Herbig and Kramer, 1994;
Jacoby et al., 1974; Jacoby 1977, 1984;
Malhotra, 1982
•Uncertainty of information (info needed vs. info
available)
Schneider, 1987; Tushman and Nadler,
1978
•Diversity of information and number of alternatives
increase
Bawden, 2001; Iselin, 1988; Schroder
et al., 1967
•Ambiguity of information Schneider, 1987; Sparrow, 1999
•Novelty of information Schneider, 1987
•Complexity of information Schneider, 1987
•Intensity of information Schneider, 1987
•Dimensions of information increase Schroder et al., 1967
•Information quality, value, half-life Sparrow, 1998, 1999
•Overabundance of irrelevant information Ackoff, 1967
Task and process parameters •Tasks are less routine Tushman and Nadler, 1975
•Complexity of tasks and task interdependencies Tushman and Nadler, 1975
•Time pressure Schick et al., 1990
•Task interruptions for complex tasks Speier et al., 1999
•Too many, too detailed standards (in accounting) Schick et al., 1990
•Simultaneous input of information into the process Grise and Gallupe, 1999, 2000
•Innovations evolve rapidly—shortened life cycle Herbig and Kramer, 1994
•Interdisciplinary work Bawden, 2001
Organizational design •Collaborative work Wilson, 1996
•Centralization (bottlenecks) or disintermediation
(information searching is done by end users rather than
by information professionals)
Schneider, 1987
•Accumulation of information to demonstrate power Edmunds and Morris, 2000
•Group heterogeneity Grise and Gallupe, 1999
•New information and communication technologies (e.g.,
groupware)
Bawden, 2001; Schultze and Vandenbosch,
1998; Speier et al., 1999
Information technology •Push systems Bawden, 2001
•E-mails Bawden, 2001
•Intranet, extranet, Internet Bawden, 2001
•Rise in number of television channels Edmunds and Morris, 2000
•Various distribution channels for the same content Edmunds and Morris, 2000
•Vast storage capacity of the systems Schultze and Vandenbosch, 1998
•Low duplication costs Schultze and Vandenbosch, 1998
•Speed of access Schultze and Vandenbosch, 1998
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THE CONCEPT OF INFORMATION OVERLOAD: REVIEW 333
TABLE 4
Symptoms or effects of information overload
Symptoms References
Limited information search and
retrieval strategies
•Search strategies through information sets
become less systematic (this is less true for more
experienced searchers)
Swain and Haka, 2000
•Limited search directions Cook, 1993
•Move from compensatory search patterns to
noncompensatory search patterns
Cook, 1993
•Identification and selection of relevant
information becomes increasingly difficult
Jacoby, 1977; Schneider, 1987
•Difficulties to reach target groups (sender
perspective)
Herbig and Kramer, 1994
Arbitrary information analysis
and organization
•Overlapping and inconsistent information
categories
Eppler, 1998
•Ignore information and be highly selective
(omission)
Bawden, 2001; Edmunds and Morris,
2000; Herbig and Kramer, 1994; Hiltz
and Turoff, 1985; Sparrow, 1999
•Loss of control over information Bawden, 2001; Wurman, 1990
•Lack of critical evaluation (become too
credulous) and superficial analysis
Shenk, 1997; Schick et al., 1990;
Schultze and Vandenbosch, 1998
•Loss of differentiation Schneider, 1987
•Relationship between details and overall
perspective is weakened and peripherical cues
get overestimated
Owen, 1992; Schneider, 1987
•Higher time requirements for information
handling and time delays
Jacoby, 1984; Hiltz and Turoff, 1985
•Abstraction and necessity to give meaning lead
to misinterpretation
Sparrow, 1999; Walsh, 1995
Suboptimal decisions •Decision accuracy/quality lowered Malhotra, 1982; Jacoby, 1984; Hwang
and Lin, 1999
•Decision effectiveness lowered Schroder et al., 1967
•Inefficient work Bawden, 2001
•Potential paralysis and delay of decisions Bawden, 2001; Schick et al., 1990
Strenuous personal situation •Demotivation Baldacchino et al., 2002
•Satisfaction negatively affected Jacoby, 1984; Jones, 1997
•Stress, confusion, and cognitive strain Jones, 1997; Malhotra, 1982; Schick
et al., 1990
•Lacks to learn since too little time is at
disposition
Sparrow, 1999
•Greater tolerance of error Sparrow, 1999
•Lack of perspective Schick et al., 1990
•Sense of loss of control leads to a breakdown in
communication
Schneider, 1987
•False sense of security due to uncertainty
reduction (overconfidence)
Meyer, 1998; Jacoby, 1984; O’Reilly,
1980
information (Jacoby, 1977), becomes highly selective and
ignores a large amount of information (Bawden, 2001;
Herbig & Kramer, 1994; Sparrow, 1999), has difficulties in
identifying the relationship between details and the overall
perspective (Schneider, 1987), needs more time to reach
a decision (Jacoby, 1984), and finally does not reach a
decision of adequate accuracy (Malhotra, 1982). Because
of these many potential negative effects, it is important to
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334 M. J. EPPLER ET AL.
devise effective countermeasures. They should address not
only the symptoms of information overload but also its
causes. In the next subsection we provide an overview of
such mechanisms.
Countermeasures Against Information Overload
Literature on information overload not only discusses ma-
jor causes and effects, but also proposes possible effec-
tive countermeasures to address the issues related to in-
formation overload. These countermeasures range from
general suggestions concerning attitude to very specific
software tools (such as filtering agents, automatic sum-
marizers, or visualization algorithms) that help to process
large amounts of information. A list of countermeasures
mentioned in the literature can be found in Table 5, which
uses the same organizational schema that was used to clas-
sify the causes, so that the two (causes and countermea-
sures) can be directly related to one another (keeping in
mind possible side effects).
With regard to information itself, information overload
can be reduced if efforts are made to assure that it is of
high value, that it is delivered in the most convenient way
and format (Simpson & Prusak, 1995), that it is visual-
ized, compressed, and aggregated (Ackoff, 1967; Meyer,
1998), and that signals and testimonials are used to min-
imize the risks associated with information (Herbig &
Kramer, 1994). On the individual level, it is important to
provide training programs to augment the information lit-
eracy of information consumers (Bawden, 2001; Koniger
& Janowitz, 1995; Schick et al., 1990) and to give em-
ployees the right tools so that they can improve their time
(Bawden, 2001) and information management (Edmunds
& Morris, 2000) skills. As far as improvements for the
organizational design are concerned, various authors take
on conflicting positions. While earlier contributions stress
the importance of self-contained tasks and lateral relation-
ships (Galbraith, 1974), more recent studies see this fo-
cus on collaborative and interdisciplinary work as a cause
rather than as a countermeasure of information overload
(Bawden, 2001; Wilson, 1996). If the cause of informa-
tion overload relates to process problems, several authors
suggest standardization of operating procedures (Bawden,
2001; Schick et al., 1990; Schneider, 1987), collabora-
tion with information specialists within the process teams
(Edmunds & Morris, 2000), and use of facilitators or col-
laborative tools (such as virtual team rooms) as “pro-
cess enablers” for cognitive support (Grise & Gallupe,
1999/2000). Finally, at the level of information technol-
ogy,several authors advocate the use of intelligent infor-
mation management systems for fostering an easier pri-
oritization of information (Bawden, 2001; Meyer, 1998;
Schick et al., 1990) and providing quality filters (Ack-
off, 1967; Edmunds & Morris, 2000; Grise & Gallupe,
1999/2000). Examples of such intelligent systems are de-
cision support systems (DSS) that reduce a large set of
options to a manageable size (Cook, 1993).
In the survey just described we can see that many au-
thors list a multitude of possible countermeasures, but that
they do not provide specific suggestions on how to com-
bine organizational, technological, personal, and infor-
mation- and task-based improvement actions. Clearly, a
systematic methodology (comparable to other standard-
ized problem solving approaches) to prevent or reduce
information overload is still missing. Such a methodol-
ogy should combine insights from various disciplines to
provide effective countermeasures that can be adapted to
various contexts. For example, insights from consumer
research on the importance of branding for reducing in-
formation overload can be used for new MIS instruments
(Berghel, 1997; Jacoby et al., 1974). Such prescriptive
suggestions must be based on rigorous empirical research.
The next subsection outlines how our framework can be
employed to conduct such empirical research.
Testable Models Derived from the Framework
The framework just presented serves primarily as an ori-
enting map for understanding and examining the overall
scope of information load research across different dis-
ciplines. However, it can also serve as a basis for future
empirical research. For instance, three testable models can
be derived from the framework.
The first testable model operationalizes the five cause
categories as independent variables that lead to (or pre-
dict) information overload (the dependent variable). Each
cause group consists of the individual items described in
the causes summary table (see Table 3). The data are col-
lected via questions asked in a Likert-scale manner. In this
way, the correlation between causes and the occurrence of
information overload (measured as the subjective feeling
of not being able to process all relevant information in the
available time) can be measured. In addition, a question-
naire based on this model can be used to test whether we
have allocated the individual causes to the right cause cat-
egory (based on goodness of fit or Cronbach alpha values).
The second testable model relates to the possible symp-
toms of information overload. The symptoms that are listed
in Table 4 can be converted into questions. Based on ques-
tionnaire results, one can then build groups of symptoms
through factor analysis and correlate these groups (and the
individual symptoms) with the question regarding over-
load (e.g. “Do you feel that you suffer from information
overload?”). This can help us understand which symp-
toms may be most representative of the overload phe-
nomenon and thereby validate our symptom categories. In
this model, the independent variables would be the identi-
fied symptoms, whereas the dependent variable would be
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THE CONCEPT OF INFORMATION OVERLOAD: REVIEW 335
TABLE 5
Countermeasures against information overload
Countermeasures References
Personal factors •Improve personal time management skills and techniques Bawden, 2001
•Training programs to augment information literacy:
information-processing skills such as file handling, using
e-mail, classification of documents, etc.
Bawden, 2001; Jones, 1997;
Schick et al., 1990; Koniger
and Janowitz, 1995
•Improve personal information management Edmunds and Morris, 2000
•Systematic priority setting Schick et al., 1990
•Improve the screening skills for information Van Zandt, 2001
Information characteristics •Raise general quality of information (i.e., its usefulness,
conciseness) by defining quality standards
Allert, 2001; Keller and Staelin,
1987; Meglio and Kleiner,
1990; Simpson and Prusak,
1995
•Focus on creating value-added information Simpson and Prusak, 1995
•Promulgation of rules for information and communication
design (e.g., e-mail etiquette)
Bawden, 2001
•Compress, aggregate, categorize, and structure information Ackoff, 1967; Grise and Gallupe,
1999/2000; Hiltz and Turoff,
1985; Iselin, 1988; Koniger and
Janowitz, 1995; Scammon,
1977
•Visualization, the use of graphs Chan, 2001; Meyer, 1998
•Formalization of language Galbraith, 1974
•Brand names for information Berghel, 1997
•Form must follow function must follow usability Herbig and Kramer, 1994
•Simplify functionalities and design of products Herbig and Kramer, 1994
•Customization of information Ansari and Mela, 2003; Berghel,
1997; Meglio and Kleiner, 1990
•Intelligent interfaces Bawden, 2001
•Determine various versions of an information with various
levels of detail and elaborate additional information that
serves as summaries
Denning, 1982
•Organize text with hypertext structures or gophers Nelson, 2001
•Interlink various information types (as internal with
external information)
Denton, 2001; Meglio and
Kleiner, 1990
Task and process parameters •Standardize operating procedures Bawden, 2001; Schneider, 1987;
Schick et al., 1990
•Define decision models developed for specific decision
processes (e.g., decision rules)
Ackoff, 1967; Chewning and
Harrell, 1990
•Install an exception-reporting system Ackoff, 1967
•Allow more time for task performance Schick et al., 1990
•Schedule uninterrupted blocks of time for completing
critical work
Sorohan, 1994
•Adequate selection of media for the task Schick et al., 1990
•Handle incoming information at once Sorohan, 1994
•Collaboration with information specialists within the teams Edmunds and Morris, 2000
•Bring decisions to where information exists when this
information is qualitative and ambiguous
Galbraith, 1974
•Install process enablers for cognitive support Grise and Gallupe, 1999/2000
•Use simpler information-processing strategies Schick et al., 1990
(Continued on next page)
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336 M. J. EPPLER ET AL.
TABLE 5
Countermeasures against information overload (Continued)
Countermeasures Reference
•Regulate the rate of information flow Grise and Gallupe, 1999, 2000
•Search procedures and strategy Ackoff, 1967; Bawden, 2001; Meyer,
1998; Olsen et al., 1998; Revsine,
1970
•Define specific, clear goals for the information in order to
contextualize it and turn it meaningful
Baldacchino et al., 2002; Denton,
2001; Meglio and Kleiner 1990
•Communicate information needs to providers Meglio and Kleiner, 1990
•Provide incentives that are directly related with decisions
in order to make decision relevant information be
processed more effectively
Tuttle and Burton, 1999
•Install a measurement system for information quality Denton, 2001
Organizational design •Coordination through interlinked units Tushman and Nadler, 1978
•Augment info processing capacity through chances in org.
design
Galbraith, 1974; Schick et al., 1990;
Tushman and Nadler, 1978
•Creation of lateral relationships (integrate roles, create
liaisons between roles, teamwork etc.)
Galbraith, 1974
•Coordination by goal setting, hierarchy, and rules
depending on frequency of exceptions (uncertainty)
Galbraith, 1974
•Creation of self-contained tasks (reduced division of
labor, authority structures based on output categories) →
autonomous groups
Galbraith, 1974
•Reduce divergence among people (e.g., with regard to
expectations) trough socialization (e.g., frequent
face-to-face interactions)
Schneider, 1987
•Install appropriate measures of performance Ackoff, 1967
•Hire additional employees Schick et al., 1990
•Create slack resources Galbraith, 1974
Information technology
application
•Intelligent information management (prioritization) Bawden, 2001; Meyer, 1998; Schick
et al., 1990
•Install voting structures to make users evaluate the
information
Denning, 1982; Hiltz and Turoff, 1985
•Prefer push to pull technologies Edmunds and Morris, 2000; Denning,
1982; Friedmann, 1977; Herbig and
Kramer, 1994
•Facilitator support through (e-)tools Grise and Gallupe, 1999, 2000
•Decision support systems should reduce a large set of
alternatives to a manageable size
Cook, 1993
•Use natural language processing systems (search with
artificial intelligence)
Nelson, 2001
•Information quality filters Ackoff, 1967; Bawden, 2001;
Denning, 1982; Edmunds and
Morris, 2000; Grise and Gallupe,
1999, 2000; Hiltz and Turoff, 1985;
Jones, 1997
•Intelligent data selectors (intelligent agents) Berghel, 1997; Edmunds and Morris,
2000; Maes, 1994
•Use systems that offer various information organization
options (e.g. filing systems)
Hiltz and Turoff, 1985; Sorohan, 1994
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THE CONCEPT OF INFORMATION OVERLOAD: REVIEW 337
the occurrence of information overload (in the opinion of
the respondents).
The third testable model addresses possible counter-
measures against information overload. It uses the five
(cause) categories to ask respondents about countermea-
sures that may or may not be in place in their organization
(and that may or may not help fight overload). Based on the
survey results, the effectiveness of these countermeasures
(as well as their grouping) can be evaluated. The inde-
pendent variables are the already implemented counter-
measures in a company, whereas the dependent variable is
the occurrence of information overload for the questioned
individuals.
The main challenge in developing these three models
is adequately converting the factors we have found in the
literature to scaleable questions that can be answered ac-
curately (and honestly) by the respondents.
The framework presented so far gives a systematic over-
view on the major findings of scientific research on infor-
mation overload. The discussion on how our framework
can be tested with the help of three individual models indi-
cates how future studies in the field can proceed. In order to
generate further suggestions on the future of information
overload research, we next go beyond the mere descrip-
tion of the field and analyze its inherent discourse patterns.
This will enable us to see other development needs and ne-
glected areas.
Biases and Tendencies in the Literature
In order to characterize the four literature domains, we
employ two visualization formats: the publication or ci-
tation timeline for the analysis of the impact of relevant
authors in various management domains and the nature
of their contribution, and the discipline Venn diagram for
the analysis of interdisciplinary research on the topic to
FIG. 4. Timeline of publications and citations of information overload studies in the area of marketing.
gain a deeper understanding of the information overload
phenomenon.
The Publication Timeline: Overload Research
Patterns by Discipline
The timeline diagram does not focus on particular con-
structs, but on the authors and their impact. It is a good
visualization tool if the historic or process perspective of a
discourse is analyzed. We have drawn a timeline diagram
for each one of the four areas in which information over-
load research has primarily been conducted over the last 30
years, namely, accounting, marketing, organizational be-
havior, and management information systems (MIS). The
objective is not to map out all the articles per field and
show all the references to other overload articles, since the
resulting diagrams would get too crowded and loose clarity
and insight. The goal instead is to foreground major con-
tributions. To determine the “relevant” contributions, we
have limited ourselves to articles that were cited repeatedly
by other articles. In the following subsections, we look at
each domain timeline in detail and provide suggestions for
future research.
Marketing
Information overload within marketing, or more specifi-
cally within consumer research, has become a critical issue
since the explosion in the number of brands in the early
seventies. Figure 4 reveals that only a few studies have
been done on a conceptual level and almost all the over-
load research in marketing is of empirical nature. This may
lead to slower, but more rigorous, theoretical progress. For
their theoretical base, the marketing researchers rely on
the findings of psychologists and cognitive scientists, in
particular on Miller’s study on our limited capacity for
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338 M. J. EPPLER ET AL.
information processing (Miller, 1956). Moreover, the em-
pirical research is, with the only exception of Muller
(1984), exclusively based on experiments and neglects sur-
veysorcase studies.
The tangled structure of the references reflects the in-
tense debate that occurred around the Jacoby et al. first
study. The methodology employed by them was contested
by Wilkie (1974), Scammon (1977), Malhotra (1984), and
others. Jacoby and Malhotra emerge to be the gurus within
the field. The most intense period of research on informa-
tion overload was from the mid-1970s to the mid-1980s.
The main question that preoccupied the researchers was
whether the number of brands and their attributes (infor-
mation load) influence product choice of consumers. Gen-
erally, the research in the field of marketing focuses on
the impact of information overload on decision quality, on
decision time, and on the actual number of information
items that can be processed in a typical purchase situation.
As a result of this focus, the information overload litera-
ture in the marketing domain neglects vital issues such as
skills, timing, and technological and organizational issues.
Nevertheless, the marketing discipline has legitimized the
research on information overload by experimentally doc-
umenting the inverted U-curve effect.
Accounting
The timeline of the contributions from the field of ac-
counting (Figure 5) presents a similar picture as the one
of marketing, insofar as the conducted research is almost
exclusively empirical. Again, the theoretical basis is bor-
rowed from psychologists and cognitive scientists such
as Schroder et al. (1967), Miller (1956), and Simon and
Newell (1971). Apart from these fundamental insights
from psychology, the research is not particularly inter-
disciplinary. Schick et al. (1990) and to a smaller extent
also Tuttle and Burton (1999) are exceptions to this gen-
FIG. 5. Timeline of publications and citations of information overload studies in the area of accounting.
eral trend. Both articles include extensive literature re-
views and contain important insights from organization
researchers as well as from MIS scholars. Similar to the
case of marketing, the empirical research in accounting is
based on experimental situations and not on field research
in organizations. Additionally, Figure 5 shows that Casey,
Iselin, and Abdel-Khalik are authors with a high impact
on the studies of information overload in accounting. As a
tendency, the researchers who conduct empirical research
often refer to conceptual studies, but the latter rarely refer
to the former. This, however, would be crucial for generat-
ing consistent theoretical progress in the study of overload
in accounting. The main theme of accounting studies is the
impact of information load on decision quality or accuracy
for matters regarding budgeting decisions (as in Swain &
Haka, 2000) or predictions of bankruptcy (as in Casey,
1980).
Organization Science
What is striking in the area of organization science is
that almost all the contributions on information overload
are conceptual articles. The few empirical papers include
O’Reilly (1980) and Griffeth, Carson, and Marin (1988).
These two studies work with a subjective definition of in-
formation overload and focus on the satisfaction of the per-
son experiencing information overload. The measurement
tools they employ are questionnaires and not experiments.
Figure 6 depicts a rather loosely connected structure
of citations, in which Galbraith and Tushman and Nadler
have prominent positions. The main reason for this loose-
ness of structure is that the authors refer to organization
scientists who made important contributions for general
organizational issues, but not specifically in information
overload-related topics. These contributions are therefore
not visible in the diagram. The most intense research ac-
tivity took place in the 1990s. Possible reasons for this
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THE CONCEPT OF INFORMATION OVERLOAD: REVIEW 339
FIG. 6. Timeline of publications and citations of information overload studies in the area of organization science.
heightened interest in the 1990s include the rapid propa-
gation of the Internet and other information technologies,
as well as the trend toward collaborative work and flat
hierarchies (Meyer, 1998). The organization science re-
searchers are mainly interested in showing whether and
how the information-processing capacity of an individual
can be expanded through changes in the organizational de-
sign and how this design influences the information pro-
cessing requirements. Again, what has been said for the
other research areas is also true for organization science,
namely, that the research in this domain is not highly in-
terdisciplinary. This is surprising for a field that typically
incorporates many concepts from related social sciences.
Management Information Systems
Surprisingly, MIS has not been the discipline that has dealt
with information overload in the most extensive manner.
Authors in the field of MIS mostly use the concept of
FIG. 7. Timeline of publications and citations of information overload studies in the area of MIS.
information overload as a starting point for their technol-
ogy application discussions. Information overload per se
is mostly not systematically defined, discussed, or ana-
lyzed, but seen as a given problem that has to be resolved.
Consequently, the net number of articles dealing primarily
with information overload in the MIS field is remarkably
low when compared to the total number of MIS papers that
address the phenomenon in their title or abstract.
The major publication activity occurred in the 1990s
(except for Ackoff, 1967; Denning, 1982; and Hiltz &
Turoff, 1985) (Figure 7). In spite of this fact—and with the
exception of Schultze and Vandenbosch’s article (1998)
that combines insights from accounting, marketing, and
organization science—the MIS researchers do not seem to
profit enough from already existing information overload
studies outside of their field. As mentioned earlier, the
focus of MIS researchers has been to propose effective
countermeasures, and not to study the root causes of the
problem or its contextual factors.
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340 M. J. EPPLER ET AL.
Consequently, the MIS research is concentrated on con-
ceptual studies and there is an obvious missing link
between conceptual and empirical studies; the two app-
roaches do not often refer to one other. One very valu-
able exception is again the contribution of Schultze and
Vandenbosch (1998), which combines both a literature re-
view and a survey. The article refers to conceptual papers
as well as to empirical findings from other areas outside the
MIS domain. Aside from this exception, MIS researchers
tend to be mainly interested in finding technical solutions
for the information overload problem. Their contributions
are thus interesting with regard to technology-based coun-
termeasures against information overload.
From the analysis of the different time lines several con-
clusions can be drawn. One is that the transfer between em-
pirical and conceptual studies can be improved and should
be intensified in future research.
Most of the empirical research that has been conducted
within the aforementioned disciplines is done in experi-
mental settings and hence does not rely on authentic man-
agement contexts. Interestingly, some research areas focus
more on empirical studies and lack conceptual research,
which is true for accounting and marketing, while the ar-
eas of organization science and MIS are more interested
in conceptual approaches. But all the four areas, except
to some extent the area of accounting, do not achieve a
FIG. 8. Cross-referencing among major information overload studies.
consistent transfer from empirical to conceptual research
and vice versa. This, however, is a crucial prerequisite
for cumulative research. Another prerequisite for cumula-
tive research is the transfer of research findings between
closely related disciplines. This important issue is further
explored in the next section.
The Status of Interdisciplinary Information
Overload Research
The Venn diagram depicted in Figure 8 maps the cross-
citations between major overload articles. The inclusion
criteria are the same ones as for the publication timelines.
It facilitates an examination of the interdisciplinary status
of information overload research.
In general, only a few authors integrate various man-
agement perspectives to study the problem of informa-
tion overload. In fact, there are no intersections between
the area of accounting and either marketing or MIS to
our knowledge. Similarly, there is no intersection between
marketing and MIS. Most of the intersections (in terms
of citing and using relevant work from other domains)
are visible within the area of organization science. Some
authors of the other three fields integrate findings from
organization science. The diagram does not lay out the
entire scope of interdisciplinary research, because it does
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THE CONCEPT OF INFORMATION OVERLOAD: REVIEW 341
not show whether authors integrate perspectives of other
research disciplines, such as cognitive science or psychol-
ogy. Clearly, future studies should draw more extensively
on existing research in other contexts (Akin, 1997).
CONCLUSIONS
In conclusion, we discuss some of the limitations of our
approach and we highlight implications of our analysis for
future research on information overload.
The limitations of this review article relate to its method-
ology and scope. In terms of methodology, the approach
we have chosen is a qualitative, inductive one with a fo-
cus on surfacing the major categories in the overload dis-
course. A bibliometric approach could have revealed more
detailed results regarding the impact of certain overload
contributions, and a hypothesis-based method would have
led to a greater focus in the article. Our aim, by contrast,
has been to provide a broad overview of the main dis-
course elements in four business-related fields. In terms of
scope, it is clear that the four fields we reviewed are not the
only areas where information overload is a major concern.
Library studies, pedagogy, military studies, and entertain-
ment are other domains that could have been included in
the review. Our focus, however, has been on central disci-
plines of business-related research. Based on the reviewed
literature in these four fields, several directions for future
research can be envisioned.
One, we need to employ alternative research methods
that can be used to study the phenomenon. Our review
shows that information overload has mainly been studied
via experiments with the exception of a few studies that
used surveys, qualitative interviews, click-through anal-
ysis, document analysis, and formal modeling methods.
Because of this dominant focus on experiments, we sug-
gest that other research methods should be employed in
order to triangulate prior findings. Such methods could
include ethnographies, action research, case studies, and
longitudinal studies, all of which capture more of the con-
textual side of the overload problem than experiments.
These inductive methods can then lead to more informed
hypotheses and refined experiments. A longitudinal ap-
proach could for example be used to examine the effects
of prolonged overload on an organization and on the pro-
cessing capacity of its employees.
Two, we need to examine ways of increasing the amount
of cross-fertilization in information overload research. As
we have noted at various points in this article, truly inter-
disciplinary approaches are not very common in informa-
tion overload research. One of the reasons for this, and—
we suspect—for the lack of transfer among empirical and
conceptual studies, is that conducting interdisciplinary re-
search increases the degree of information (over)load for
the researchers themselves (Bawden, 2001, p. 9). In or-
der to keep up with the developments in their field, re-
searchers have to specialize and limit their research scope.
Here editors and reviewers have a vital role to play. They
can inform researchers about related and relevant findings
that have been excluded from the researcher’s focus area.
Editors may also occasionally ask reviewers from other
disciplines to evaluate submitted articles so that they can
provide suggestions from other fields. Another approach
could be to create dedicated interdisciplinary journals that
encourage contributions that cross traditional disciplinary
boundaries (such as The Information Society).
This push toward interdisciplinarity does not have to
lead to an identity crisis of a discipline such as MIS
(Benbasat & Zmud, 2003) if the individual disciplines are
aware of their relative strengths and weaknesses regard-
ing a particular research topic. As shown in our review
article, each one of the four domains has its advantages
and drawbacks for the study of information overload. The
advantage of MIS studies on information overload, for
example, is their focus on solutions and on the effects of
new information technology on the individual, the group,
and the organization. However, it may have overlooked
some of the organizational parameters and their role in in-
creasing or decreasing information overload. Organization
science can provide insightful suggestions on this score
(such as the effect of decentralization on the amount of in-
formation that needs to be communicated and processed)
leading to more realistic information technology (IT) solu-
tions. On the other hand, the organizational point of view
may lack insights on the individual’s reactions to such
changes. This, in turn, is where the experimental studies
of accounting and marketing can provide helpful findings
and methodologies. These insights can be combined and
operationalized in empirical investigations, for example,
regarding the effects of e-mail load and e-mail policies on
worker productivity, decision quality, and communication
behavior.
Such interdisciplinary approaches to the study of over-
load may, however, require research projects based on
interdisciplinary teams that combine the talents of (for ex-
ample) MIS, accounting, and organization science schol-
ars. They may reduce the potential overload for the indi-
vidual researcher, as he or she can focus on his or her area
of expertise while incorporating insights from other areas
through other team members. The reasons why such in-
terdisciplinary research teams are not more common are
manifold and include existing research habits, assumptions
and methods, and institutional barriers, as well as com-
munication and terminology problems. Nevertheless, the
overload problem calls for interdisciplinary approaches as
many of the open research questions in this field cross
traditional disciplinary boundaries (from understanding
individual coping behavior to designing organizational
countermeasures).
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342 M. J. EPPLER ET AL.
One such open research question relates to the interrela-
tionships highlighted in our conceptual framework, specif-
ically the reciprocal effects of technological, personal,
information-based, task-oriented, and organizational
changes. Our framework and its derived models for sur-
vey research on causes, symptoms, and countermeasures
can be used for such purposes. This can lead to a rank-
ing that distinguishes high-impact causes and countermea-
sures from low-impact causes and inefficient countermea-
sures. Although the tables in this article provide a good
overview of possible causes and countermeasures, they do
not yet qualify or prioritize these factors. Future research
should thus examine the interrelationships between the
listed causes and countermeasures in more detail. This
can lead to MIS solutions that address the problem drivers
and root causes of the overload issue with effective coun-
termeasures.
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