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Page 351
42
Small Manufacturing Enterprises and the National Information
Infrastructure
Robert M. Mason, Chester Bowling, and
Robert J. Niemi
Case Western Reserve University
Statement of the Problem
The vision for the future is that an emerging national
information infrastructure (NII) and its defense counterpart (DII)
will equip U.S. industry to be second to none in the global
economy. The NII will enable the U.S. industrial base to become
more agile and to operate as a highly competitive, flexible,
just-in-time, manufacture-on-demand system that facilitates free
competition and specialization among manufacturers and suppliers.
All firms, regardless of size, will have ready access to product
requirements and specifications and will be able to compete fairly
with other firms. Moreover, the NII with the DII will encourage
commercial suppliers to respond to defense needs, enabling dual use
designs and strengthening the flexibility of the nation's defense
infrastructure.
The reality is that many existing small firms are ill equipped
to participate in this vision. Moreover, there is concern that the
learning cycle for small manufacturing enterprises (referred to
here as SMEs) to implement information technology is too long and
costly for them to effectively make the transition to the NII
environment. The solution to the problem is not simply one of
assuring that every SME can purchase and install a new information
system. Instead, the solution requires an understanding of how a
complex combination of structural, technical, managerial, and
economic factors affect the diffusion of information technology in
the manufacturing sector, especially among SMEs. From the viewpoint
of our national economy, the problem is that this complex set of
factors impedes the effective implementation of information
technology in SMEs and puts at risk a significant component of the
nation's manufacturing base, a component that is responsible for up
to nearly 40 percent of the nation's manufacturing employment.
Developing nations may "leapfrog" over the United States and other
advanced nations if our established enterprises are unable to
change quickly enough. The purpose of this paper is to help
understand this set of factors and to explore how best to manage
the risk associated with a slow rate of diffusion of information
technology in SMEs.
Overview
The "Background" section provides a synopsis of the different
views on the role of SMEs in the nation's economy and manufacturing
infrastructure. This section also summarizes the different
frameworks within which we can understand the economic, behavioral,
structural, and technical issues associated with how SMEs may
participate in the benefits of the NII.
The "Analysis" section of the paper provides more detail on the
frameworks outlined in the Background section and examines the
prospects for SMEs to become full participants in the NII. This
section synthesizes adoption and diffusion studies and research on
the implementation of new information technologies. The emerging
framework is that of organizational learning at the level of the
firm and the concept of the supply chain (or value chain). The
learning framework enables us to make sense of the range of factors
associated with
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technology adoption, and the value chain framework illustrates
why action by an individual firm is inadequate for that firm to
realize the benefits of an NII.
The final section of the paper discusses opportunities for
national policy to alleviate the problem of SME's participation in
the NII. The paper concludes that a coordinated collaboration among
private, university, and government resources offers the best way
to assist U.S. SMEs in making the transition to electronic commerce
and the benefits of the NII.
Background
SMEs and the Economy
Small manufacturing enterprises (SMEs) are responsible for an
estimated 28 to 40 percent of the employment in the manufacturing
sector.1 Moreover, there is evidence
that SMEs are more effective at job creation2 and job replacement,3 more innovative in the development of
products and process improvements,4
and more flexible and thus more competitive in terms of the ability
to produce small quantities. All these factors may explain the
shift to a smaller average plant size.5 The claims to new job creation are
open to question—SMEs also exhibit high failure rates, and
thus new jobs may not be long-lived.6 However, others point out that small
firms will continue to add jobs because much growth will take place
in industries in which small businesses have relative advantages.7
There is no question that SMEs are a crucial element in the
nation's manufacturing base. If one believes, as many do, that
manufacturing must continue to be a foundation for U.S. economic
competitiveness,8 then SMEs will
continue to be a crucial part of this competitiveness.9 The role for small firms appears to
be increasing; there is evidence of a trend toward more of the
total production coming from smaller manufacturers.10 However, the United States is
lagging behind Europe and Japan, where small firms account for 45
to 60 percent of manufacturing employment.11
SMEs and the NII
Neither the global competitiveness of U.S. industry nor the
future role of SMEs is assured. The NII vision of preserving the
tradition of free market competition both among manufacturing
suppliers and among international companies is consistent with what
Porter12 suggests are the conditions
for global competitiveness: demanding customers who can choose from
an intensely competitive local network of suppliers.
The NII and DII are expected to enable this competition and the
development of dual use processes and designs. Large manufacturers
(including Department of Defense purchasers and contractors) can
make their specifications available online, eliminating
distribution delays and increasing the scope of distribution. In
one vision currently being articulated by the U.S. Department of
Defense (DOD), the NII and DII enable the creation of an Integrated
Data Environment (IDE) in which information itself (e.g., designs,
production methods) becomes a commodity and is traded. With
information available on both specifications and designs, firms can
work only on those opportunities for which they are most capable,
reducing the risk and costs of bidding on marginal
opportunities.
For SMEs to participate, they must have access to the NII and
they must be able to use computer technology to integrate their
business and technical functions. They must understand and use
electronic commerce technologies (ECTs). Currently, small
businesses are not utilizing computers to the degree necessary to
fully participate. A recent survey commissioned by IBM indicated
that while 82 percent of small businesses (not just manufacturers)
had desktop computers, only 37 percent had local or wide area
networks.13 In a stage model of
information technology maturity,14
almost two-thirds of these respondents would fall into the first,
most elementary, stage of maturity.
SMEs are becoming aware of the need to adopt some form of
electronic communications. With increasing frequency, prime
contractors and large firms have demanded that their suppliers have
electronic
Page 353
capabilities. As one would expect, this has heightened interest
in electronic commerce capabilities among small-and medium-sized
businesses. The interest is likely to escalate. One software vendor
executive, explaining that his company was trying to respond to
customers' needs for advice and consultation about electronic
commerce, put it this way, "Our executives have been around long
enough to tell the difference between a ripple and a wave. This one
is a wave."15
Engineers from the Cleveland Electronic Commerce Resource Center
(Cleveland ECRC) report similar interest but observe that some
small firms are satisfied with a "rip and read" solution: they link
into a bulletin board or value-added network with a personal
computer but use the computer as an expensive fax machine. They
"rip off the printed specifications," then read them and insert
them into their manual system.16
This approach works for written specs and to some degree for
drawings, but it clearly is limiting. More advanced firms install a
computer aided design (CAD) system to enable them to accept design
data in digital formats. Often, they too have a manual internal
system and do not attempt to use the digitally stored format.
Compounding the technical problem is the lack of a single
standard that is widely accepted; Chrysler, Ford, and GM use
different, incompatible CAD systems. For most SMEs, the cost of
implementing multiple standards is too high, and they either choose
a single customer's standard or opt for another market. In either
case, the situation does not lead to increased competition and to
the increased competitiveness of SMEs. A single standard would
help. Standards such as PDES/STEP are being developed, but
agreements and adoption take time, and such standards address
primarily the technical issues of data sharing.
Organizational (i.e., managerial and cultural) issues are equal
to, if not greater than, technical capabilities in importance. In
their discussion of agile manufacturing, Goldman and Nagel17 share the vision of integration of
virtual enterprises through the use of information technology,
including standards and "broad-band communications channels."18 They acknowledge the need for
flexible production machinery but point out the need for
organizational innovations as well. The agile system they envision
requires flexible production workers and managers, not just
technology. Getting the integration of technology and people into a
new, responsive system is a challenge. They conclude, "An
understanding of the nature of managerial decision-making is more
important than ever before."19
Other researchers agree with Goldman and Nagel that the
managerial, organizational, and cultural issues are at least equal
in importance to the technical challenges of tapping into the
benefits of the NII. In a field study of five large firms that were
judged to be implementing integrated information systems
successfully, a study team found six shared characteristics among
the firms, and only one (the goal of capturing all data in
electronic form at its origin) was technical.20 The other five characteristics
(vision and clear strategy, vocabulary/language incorporating
metrics shared by technical and business staff members, customer
focus, and a sense of urgency) were organizational factors.
Factors Affecting SMEs' Adoption of
Technology
One approach to understanding SMEs' use of information
technology would be to view ECT as a technology that will be
diffused throughout manufacturing. This diffusion approach21 uses the familiar S-curve to
identify the percent of SMEs that have adopted ECTs over time.
Factors associated with an individual firm's propensity to adopt
technology might suggest strategies for working with innovators,
early adopters, and so on.22
Implications of this type of model for policy are discussed further
in the final section.
Another useful approach, the one taken for the remainder of this
paper, is to seek an understanding of the decision-making process
within the SME. From this viewpoint, we may gain some insight into
the economic, technical, structural, and other barriers to adoption
as seen by the SME.
The stage model suggested by Venkatraman23 of firms' use of information
technology (Figure 1 shows an adaptation of this model) is used as
a basis for identifying the gap between the "as is" state and the
"desired" (or ''to be") state of SME capabilities.
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Figure 1
Stage model of information systems use. SOURCE: Adapted from
Venkatraman, N., 1994, "IT-enabled Business
Transformation: From Automation to Business Scope Redefinition,"
Sloan Management Review, Winter, pp. 73–87.
Page 355
The data from the IBM survey of small businesses24 indicate that almost two-thirds of
the survey respondents are in the first stage of maturity in
applying information technology. Virtually none of them have
progressed beyond the second stage, and there is no assurance that
they will go beyond this stage. For SMEs to benefit from the NII,
they must be at level 3 or above, developing capabilities for
network/supply chain integration. Although the IBM survey was not
limited to manufacturing firms, our experience with SMEs leads us
to speculate that small service firms and those in the retailing
and trade sectors may use computers even more than manufacturers,
lowering even further the estimate of how many SMEs have moved
beyond the first stage of computer use.
This stage model is descriptive, and it only indirectly suggests
how an organization moves from one stage to another. Our concern is
to understand how the organization, particularly an SME, progresses
from the applications of isolated systems to network and supply
chain integration and, more importantly, how this process can be
accelerated. The relevant fields of research are those of
technology policy, innovation adoption, the decision-making process
within the firm, and the emerging field of inquiry on
organizational learning.
The concept of organizational learning,25 particularly the use of the human
experiential learning model proposed by David Kolb26 and recently applied to
organizations,27 provides a useful
framework to interpret the findings from the other fields. This
model, shown in Figure 2, illustrates the different modes by which
an individual (organization) learns. Learning takes place in two
dimensions: in the concrete-abstract dimension (shown vertically as
a continuum) and in the active-reflective dimension (shown
horizontally). Individuals (and organizations) have different
preferences for learning and processing information in these
dimensions.28 Some prefer more
concrete and active learning (e.g., entrepreneurs); others prefer
more abstract and reflective learning (e.g., professors).
Figure 2
Experiential learning cycle. SOURCE: Reprinted from Kolb, David,
1984,
Experiential Learning: Experience as the Source of Learning
and
Development, prentice-Hall, Englewood Cliffs, N.J.
The learning cycle model suggests that only when the
organization goes through all four modes is learning complete. For
example, a firm may introduce a new process for a customer or
product line (active experimentation), collect sales and
quality data over time (concrete experience), interpret
these data and compare with prior experience (reflective
observation), and develop a projection of sales and costs of
quality if the new process were applied to all their product lines
or to all their customers (abstract conceptualization).
Based on the model, the firm may choose to switch its other
products to the new process, again moving to active
experimentation and
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restarting the cycle. By passing through each of the learning
modes, the firm generates new knowledge. The firm learns,
and the learning is not limited to the simple aggregation of
additional data or to thinking about a new idea—the cycle is
complete.
Using the concept of the learning cycle, we can frame our
concern as that of understanding the predominant learning modes of
SMEs and of understanding how SMEs can incorporate all learning
modes in their progress toward the higher stages of information
technology maturity. For this understanding, we can draw on several
areas of research about how organizations adopt technology. In each
of the relevant areas, it is evident that one must use caution in
applying concepts derived from the large organizational context to
the SME.29 However, some studies
have focused specifically on the decisionmaking and policy
formulation in the small firm, and these studies are particularly
helpful in our efforts to understand how to accelerate learning and
ECT adoption in SMEs.
Analysis
The first three subheads below outline relevant concepts from
three distinctive but overlapping areas of inquiry. Each has its
own literature base and each offers some insight into how firms,
and SMEs in particular, may implement and use information
technologies. The fourth subhead outlines the structural issues
that may initially inhibit SMEs' effective participation in the
NII. The section concludes with a synthesis of ideas about how SMEs
may approach the adoption of electronic commerce technologies and
realize the benefits from the NII.
Diffusion of Technology
The diffusion literature30
characterizes the industry adoption of new products by an S-shaped
curve. The curve reflects exponential growth with a rate that
depends on the size of the remaining market. The diffusion model
has been used with some success in technology forecasting. With
good data on when a low level of adoption has been achieved (e.g.,
5 percent), the model is effective in identifying the dates by
which a specific level of industry penetration (e.g., 50 percent)
will occur.
The S-curve model is often used to identify firms according to
when (early or late) they make the decision to adopt the
technology. The classifications may indicate different
organizational characteristics. A modification of this conceptual
model31 classifies the "buyer
profiles" as being one of five types: innovators, early adopters,
early majority, late majority, and laggards.
Recent research32 tested the idea
that psychological characteristics (e.g., attraction to technology,
risktaking) rather than economic variables might be used to discern
buyer profiles. The study found that the benefit-cost variables
were better predictors. Although one could argue with how the
variables were operationalized and with the limits of the study
(focus groups on a single product), the researchers' conclusion has
face validity: Companies that pioneer new producs must focus on the
benefits desired by purchasers. Even the early adopters, who are
less price sensitive, seek benefits that meet their needs better
than current technologies. What is not discussed in the study is
the changing nature of the benefits and costs with changes in the
organizational characteristics and with changes in risk as the
technology matures.
Kelley and Brooks33 also showed
the predictive power of economic incentives in the diffusion of
process innovations. Not surprisingly, firms with high wage rates
were more likely to adopt labor-saving technologies than were firms
with low wage rates. The key is to note that the benefits and costs
are established by the firms's perceptions; these perceptions are
affected by the organizational values and the firm's particular
situation.
As noted by Schroeder,34 the
survival of an SME is linked to the adoption of technology as a
regular part of doing business. If it is in the nation's interest
for SMEs to thrive, then the diffusion issue is how to accelerate
the adoption of information technologies among SMEs. The diffusion
model may be a useful metric by which we can track and predict
adoption rates as early data become available. However, the
diffusion model does not help explain how firm-level decisions are
made. Concepts that examine how the individual firm makes a
technology adoption decision may be more informative in the early
development of the NII.
Page 357
SME Decisionmaking
The literatures relevant to an SME's decisions on technology
adoption are those on corporate strategy, technology strategy,
technology policy, information system implementation and planning,
strategic information systems, and investment decisionmaking at the
level of the firm. These areas of study are rich in topics that are
relevant to technology adoption, but the focus on SMEs and their
adoption of technical innovations reduces the scope
considerably.
SMEs differ from large companies in how they develop their
corporate strategies and their technology policies. Large companies
typically have well-defined processes for developing and
implementing strategies through a corporate planning process. Small
firms often use less structured approaches; strategies and policies
may not be formulated but may "emerge" from a set of actions and
experiments.35
In an SME, the chief executive officer (CEO) often is
one—or perhaps the—owner of the firm. In these firms, the
CEO's viewpoint is a critical contributor to strategy and policy. A
recent study of SMEs36 showed that
implemented technology policies (not just written policies) in SMEs
are strongly influenced by how the CEO perceives the world. Even
though all the firms in the study were immersed in the same
industrial setting in the same Canadian province, the CEOs differed
in their view of how hostile and how dynamic their environment was.
The firms' propensity to invest in new technology was strongly
related to these views. The basis for decisions is not an objective
reality but rather a socially constructed reality37 as reflected in the viewpoint of the
CEO.
The social construction of the adoption decision by a firm has
other participants as well. For the SME, a strong influence is the
supplier, who may be a major source of information.38
The innovativeness of an SME is related to the firm's outward
orientation (e.g., customer focus) and the participation of the
firm's functional groups in the decision.39 There is evidence40 that the SME learns with increasing
technological capabilities so that, over time, its decisionmaking
places more weight on factors that are more closely related to the
true potential of the technology.
SME Learning
Arrow41 noted that firms learn
through experience. This learning normally is considered to be
related to process improvements and is the foundation for the
concept of reduced costs over time because of "the learning curve."
More advanced technologies may have greater productive potential,
but the firm has less expertise in implementing such technologies.
Knowing it has less expertise, the firm expects greater costs. The
firm thus faces a trade-off in its choices of technologies to
adopt.42
The capacity for learning affects the rate of adoption of new
technology. Firms that have existing technological capabilities
have higher "absorptive capacity"43
for new technology; they are able to learn more quickly.44
A firm's installed technology also affects the extent and
magnitude of benefits the firm experiences from installing new
systems. Firms that have more existing technological
capabilities—for example, firms that have implemented
information technologies in both the administrative and
engineering/production operations—enjoy benefits that are
greater than the sum of the benefits from individual systems. There
is synergy and, because of the added benefits and increased
capacity for learning, the "rich get richer" and vice versa. This
appears to be the case both for large firms45 and for SMEs.46
When a technology is new to an industry—before its
technical and economic superiority has been widely
accepted—the learning capacity of a small firm is related to
the firm's linkages with other firms and other industrial
organizations. These external linkages, many of which provide
informal but trusted conduits for sharing of technical know-how,
appear to lower the cost of learning for the firm. Kelley and
Brooks put it this way: "Small firms' propensity to adopt a process
innovation is particularly enhanced by the nature of linkages to
external resources for learning about technological
development.… Where linkages to such external learning
opportunities are particularly well-developed we would expect to
find a more rapid rate of diffusion of productivity-enhancing
process innovations to small firms."47
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Organizational learning may be "single-loop" or "double-loop."48 In single-loop learning, the
organization improves its efficiency, becoming ever better at
dealing with a prescribed problem or environmental situation. The
lowering of costs because of the ''learning curve" is an example of
single-loop learning. Double-loop learning, by contrast, is
characterized by a shift in viewpoint and a modification of basic
premises. Double-loop learning requires unlearning prior
assumptions and standard operating procedures; it involves
developing new paradigms, new frames of reference, and new
interpretive schemes. Single-loop learning reduces variability;
double-loop learning increases variability in search of more
relevant objectives or more effective strategies.
Because prior procedures and paradigms have a history of
success, organizations have difficulty engaging in double-loop
learning; they actively resist.49
However, dynamic and turbulent environments demand that firms
exhibit more variability in order to meet changing needs. One
approach to stimulating variability—and possibly double-loop
learning—is organizational restructuring. Restructuring
(changing the top management team and/or the CEO) is especially
effective when combined with a change in strategy (e.g., new
products or markets).50
SMEs, especially the smaller ones, are less likely to adopt a
restructuring approach. A turbulent environment sometimes
stimulates an SME owner to sell or merge with a larger firm. Often,
however, the SME that cannot adapt quickly enough to environmental
changes simply ceases to exist. The latter outcome contributes to
the statistics used by those who argue that SMEs provide unstable
employment, even if they do create a significant portion of new
jobs.
The learning model in Figure 2 provides a framework that helps
synthesize these issues. Since complete learning means that the
organization engages in each of the modes, an enterprise may engage
in formal or informal collaboration with external organizations to
learn. For example, the motivation for close alliances between
suppliers and manufacturers51 is
partially explained by the benefits of learning, and the higher
rate of innovation adoption because of external contacts52 may be due to the expanded learning
modes made possible by these contacts.
An alternative to restructuring or going out of business is to
establish and maintain external relationships that enable learning.
Such organizations, which "bridge"53
sources of knowledge about new technologies (e.g., universities)
and the SMEs (as potential users), have been stimulated by federal-
and state-level programs that have set up technology transfer
centers and assistance networks. Ohio's Thomas Edison Technology
Centers, the federally funded Manufacturing Technology Centers
(MTCs), and, most appropriately, the federally funded Electronic
Commerce Resource Centers (ECRCs) are examples of such bridging
organizations.
The value of such organizations was set forth over a decade ago
by Trist,54 who noted that complex
societies and rapidly changing environments give rise to "meta
problems" that a single organization is unable to solve. The
solution is the development of "referent organizations" that
mediate the interorganizational collaboration required in the
organizational domain of interest.
Although detailed studies of the effectiveness of MTCs and ECRCs
are premature given their recent formation, the political judgment
seems to be that they are effective.55 Studies of Ohio's Thomas Edison
Technology Centers generally have praised their value and
effectiveness.56 One of the
challenges noted is that of "relationship-building."57 There is the explicit acknowledgment
that the relationships and the process of technology solving are
equal to, if not greater than, the importance of developing the
technology itself. These evaluations appear to support the concept
that the bridging, or referent, organizations contribute to
learning, and that at least part of the new knowledge created is
not migratory knowledge but is embedded in the relationships that
are established and maintained.58
Implicit in the Mt. Auburn report is the notion that the
relationship-building role of these organizations is
underdeveloped.
The Structural Issue: Of What Benefit
Are a Few Telephones?
The current status of electronic commerce technology may be
similar to that of the early telephone. Imagine being given the
opportunity of purchasing the third or fourth (or even the
fiftieth) telephone: unless you are assured that the other people
(organizations) with whom you want to talk (trade/communicate) are
equipped with compatible technology, the benefits are nil. Unless
the advanced technology has its own appeal, a prudent business
decision is to "wait and see"—wait until there is a critical
mass of manufacturers and suppliers with
