Anticipation of new technologies:
supply chain antecedents and
Andrew Beheregarai Finger
Universidade Federal de Alagoas, Maceio, Brazil
Barbara B. Flynn
Kelley School of Business, Indiana University, Indianapolis, Indiana, USA, and
Ely Laureanos Paiva
Fundacao Getulio Vargas, Sao Paulo, Brazil
Purpose – The purpose of this paper is to propose and empirically validates a measure of the
anticipation of new technologies (ANT) construct, first suggested by Hayes and Wheelwright (1984).
ANT allows establishment of a sustained competitive advantage through acquiring new technologies
and the capability to use them, in advance of actual need. The theoretical foundation for ANT is
developed using the literature on absorptive capacity. Several elements of supply chain management
are proposed as antecedents to ANT.
Design/methodology/approach – Perceptual survey data from 317 manufacturing plants in ten
countries was used to test the hypotheses using structural equation modeling and confirmatory
Findings – The key supply chain antecedents of ANT are supply chain planning, internal integration
and supplier integration. ANT was related to both operational and cost performance.
Research limitations/implications – Potential limitations include the use of an existing database,
the plant as the unit of analysis and the need to include customer integration, as well as supplier
integration. The results demonstrate the competitive importance of the ANT construct and the key role
that relationships with suppliers play in its development.
Practical implications – This research sheds new light on a construct whose roots are inherently
practical. Suppliers and their extended networks are an important source of external knowledge about
technology and future customer needs, thus, supply chain relationships are an important contributor
Originality/value – Although the role of technology in establishing a competitive advantage has
been thoroughly studied, the effectiveness of developing technologies that are expected to be important
in the future has not, although this concept was first introduced almost 30 years ago. The authors use
absorptive capacity to develop the role of supply chain relationships in building an organization’s ANT
capability, contributing to the operations strategy literature by grounding a practical construct in the
theoretical literature and demonstrating its importance.
Keywords Operations strategy, Absorptive capacity, Supply chain integration,
Anticipation of new technologies
Paper type Research paper
Why do investments in technology yield big dividends for some organizations, but not
for others? Organizations invest in new technologies because they believe that they will
be instrumental in achieving reduced costs, improved flexibility, faster customer
deliveries, improved quality and other important outcomes. However, this has not
been consistently found in the literature; rather, technology investments have been
associated with improved performance in some cases (Kotha and Swamidas, 2000;
Das and Narasimhan, 2001; Fawcett and Magnan, 2002), minor or no changes
The current issue and full text archive of this journal is available at
Received 21 September 2012
Revised 3 February 2013
16 August 2013
Accepted 23 September 2013
International Journal of Operations &
Vol. 34 No. 6, 2014
rEmerald Group Publishing Limited
in performance in others (Cordero et al., 2009; Cagliano and Spina, 2000) and
declining performance in others (Chung and Swink, 2009).
Consider the example of two firms that produce a similar product. Company A
conscientiously scans the environment for new technologies, goes to trade shows and
meets with technology sales reps, in order to learn about state-of-the-art, turnkey
process technology that has a proven effect on performance. However, no matter what
sort of technology investments it makes, Company A never gains market share or
commands a price premium. Company B, on the other hand, tinkers with its existing
process technology, adapting it to meet its current needs. When considering new
technology investments, it pursues multiple leads simultaneously, sometimes going
down the wrong path and investing in technologies that do not ultimately work out.
In learning about new technologies, it goes to the same trade shows and meets with the
same sales reps as Company A, but it also talks to its suppliers to see what they
know. It asks customers about their future needs, developing and investing in process
technologies that might be useful in the future. It develops its workforce to use technologies
that it believes will be important for future generations of its products. The result?
Company B leads its market, and its processes are the standard that is benchmarked
by other companies.
Why is there such a performance difference between Company A and Company B?
Company A invests in the best process technology available for today’s products, with
impressive results. However, such technology is readily available to any competitor
with sufficient funds. At best, it can only establish technology parity with its competitors,
playing catch-up and scrambling to mimic what they are doing. It continues to find itself
unprepared for changes in its competitive environment as new challenges unfold.
Furthermore, Company A does not consider whether technology investments are aligned
with its unique strategy, history, market and problems.
Company B, on the other hand, focusses on both its current products and future
generations of products. It speculates about the manufacturing and process technology
that will be needed to support them, drawing upon knowledge that it acquires from
a wide range of sources. It filters this knowledge for alignment with its strategy and
potential relevance to the problems it currently faces and that it anticipates facing in
the future. It also develops its workforce for what its anticipated future technology
needs are. Not surprisingly, some of the leads do not pan out, and Company B
sometimes invests in technologies that are not ultimately helpful in producing its
future products. However, it is well prepared for those technologies that are relevant to
its future because it has mastered them in advance. If Company’s B’s assumptions
about its future are correct, it will have a robust competitive advantage, because it is
prepared for new technologies and customer needs when they emerge. Thus, Company
B establishes a moving target that its competitors struggle to keep up with.
We propose that organizations with the best performance understand the importance
of anticipating new technologies, thinking about changing customer needs and the
technologies and capabilities that will be needed to support them in the future.
Our research is based on the work of Hayes and Wheelwright (1984), who described the
best organizations as constantly searching for new technologies, anticipating and
preparing themselves for their implementation at some point in the future, even though
there may not be an immediate need. They suggested that organizations that anticipate
new technologies are better prepared to implement them when needed and to exploit
them as a source of competitive advantage. Although Hayes and Wheelwright (1984)
described anticipation of new technologies (ANT) as a key characteristic of world class
manufacturers, this construct has not been empirically validated nor positioned in the
This research focusses on two research questions. First:
RQ1. What is the relationship between ANT and competitive performance?
RQ2. How can an organization nurture its capability to anticipate new
We propose that supply chain management is important in developing this capability,
because suppliers can be a potent source of ideas about technologies that may be important
in the future, particularly as they work with their extended networks. We use absorptive
capacity to explain the importance of supply chain management in nurturing ANT.
We begin by describing the ANT construct and articulating its key characteristics,
based on Hayes and Wheelwright (1984). We draw upon the organizational theory
literature on absorptive capacity to draw parallels with ANT and set the stage for
describing the role that supply chain integration can potentially play in supporting ANT.
Hypotheses are tested using a sample of 317 manufacturing plants in ten countries.
Although originally introduced by Hayes and Wheelwright (1984), the ANT construct
offers significant potential for organizations facing dynamic competitive
environments. Hayes and Wheelwright (1984) described ANT as a distinguishing
trait of world class manufacturers, whose competitive strategy is based on their
manufacturing capabilities. ANT is the “extent to which an organization anticipates
the new technologies that will be important to it in the future, acquires them and
develops capabilities for implementing them, in advance of actual need” (Hayes
and Wheelwright, 1984).
There are several key characteristics of ANT. First, ANT is based on an
organization’s anticipated future needs. While a well-run organization like Company A
may do extensive technology development for its current products, an organization
that is skilled in ANT, such as Company B, also continually invests in the process and
manufacturing technologies that it believes will benefit its future generations of
products (Hayes and Wheelwright, 1984; Maier and Schroeder, 2001). Thus, it must be
able to anticipate what its customers’ future needs will be, which future products will
satisfy these needs, which new technologies will be most relevant in supporting them
and which new capabilities will be needed to effectively deploy them. Thus, successful
ANT requires having a good understanding of future generations of customers and
products, having the resources and foresight to acquire new technologies in advance of
need and developing capabilities to implement them in a way that aligns with future
goals and objectives.
Second, ANT focusses on both investments in technologies and development
of capabilities; thus, it has both a “hard” and “soft” side. Both are critical, because
investments in technology are readily imitable by competitors with deep enough
pockets; technology, alone, is “a great equalizer, eroding the competitive advantage of
even well-entrenched firms and propelling others to the forefront” (Porter, 1985, p. 93).
Although an organization like Company A may seize a temporary competitive
advantage by investing in state-of-the-art process and manufacturing technology:
[y] if this [y] comes to be regarded as a goal in and of itself, if the organization does not
immediately begin experimenting and tinkering with it, pushing it to do things for which it
wasn’t intended (but which it might eventually accommodate), the advantage is soon lost [y]
Their energy spent, they watch in frustration and helplessness as their world class
competitors relentlessly march past them (Hayes et al., 1988, p. 25).
Thus, the combination of hard investments and tacit capabilities makes ANT difficult
Third, ANT can be costly. It involves the development and acquisition of
technologies that may or may not actually be relevant in the future, thus, substantial
capital, time and other resources are required. Because some of the technologies that
it had believed would be critical in the future may never actually materialize or may
turn out to be unimportant to its strategy, an organizations that is less skilled in
ANT may have costly false starts, wasting significant time and money. Thus,
ANT can be a risky and costly strategy. However, organizations that are skilled
in ANT have a significant competitive advantage because they have invested in
appropriate new technologies and developed the necessary capabilities in advance of
need, causing competitors like Company A to scramble to catch up. Thus, while the
risks associated with ANT are significant, the potential benefits are a potent source
of competitive advantage.
Relationship between ANT and absorptive capacity
Cohen and Levinthal’s (1990) absorptive capacity construct provides a theoretical
foundation for ANT. Absorptive capacity is the ability to acquire and assimilate
knowledge and utilize it effectively, in order to achieve better performance (Robinson
and Sutbberud, 2011; Jabar et al., 2011; Kogut and Zander, 1993; Jansen et al., 2005).
We view ANTas a specific case of absorptive capacity. While absorptive capacity
focusses on knowledge, ANT focusses on a specific type of knowledge: knowledge
about both hard technologies and tacit capabilities for effectively implementing them.
In addition, absorptive capacity does not differentiate between knowledge relevant
to current problems and knowledge that will be relevant in the future, while
ANT is specifically oriented toward the future. Nonetheless, the absorptive capacity
construct provides a useful framework for understanding ANT and the role
that supply chain management plays in acquiring, assimilating, transforming
and exploiting external knowledge to effectively anticipate new technologies. In the
following sections, we describe relevant concepts from the absorptive capacity
literature, then apply them to ANT.
Zahra and George (2002) described two broad categories of absorptive capacity.
Potential absorptive capacity is the capability to acquire and assimilate external
knowledge, while realized absorptive capacity is the capability to transform and
exploit knowledge that has been acquired and assimilated.
Potential absorptive capacity. Acquisition. According to the absorptive capacity
literature, acquisition is the ability to identify and acquire externally generated
knowledge (Zahra and George, 2002). Determining the proper amount of acquisition is
a balancing act between pursuing too many costly leads and ignoring leads that have
potential; ideas and discoveries that fall beyond the search zone can be easily
overlooked by an organization that is unable to relate to them (Zahra and George, 2002).
In ANT, acquisition focusses on knowledge about technologies that may be relevant
in the future, including both existing technologies that may be important to future
products and technologies that are still being developed. Acquisition begins
with recognition of the strategic importance of being ahead of competitors in
implementing new technologies, providing the impetus for scanning the external
environment for new manufacturing and process technologies that may hold
potential (Hayes and Wheelwright, 1984). Because technologies that have not yet
been refined or developed may hold the key to future success, it is important that
acquisition focusses on both traditional sources of external knowledge, such as trade
shows and technology sales reps, and non-traditional sources, such as suppliers and
their extended networks.
Assimilation. According to the absorptive capacity literature, assimilation consists
of analyzing, processing, interpreting and developing an understanding of external
knowledge (Zahra and George, 2002). Once it has been acquired, knowledge is
transmitted across organizational boundaries (Liao et al., 2003), where it is transformed
and communicated to relevant departments and individuals. Interactions between
people with diverse knowledge enhance the ability to make novel linkages and
associations during this process (Cohen and Levinthal, 1990). Thus, internal networks
are important for transferring knowledge between individuals and across functional
The concept of assimilation applies well to ANT, whose filtering function is critical
in assessing the future potential of new technologies. Rather than selecting between
proven state-of-the-art alternatives, organizations address questions related to the
composition of their future markets and products, uncertainties about the viability of
technologies that are still under development, and the appropriateness of technologies
used in current applications to future needs. Without the ability to filter potential
new technologies so that it only pursues those with the greatest relevance to its future,
an organization can be vulnerable to pursuing dead-end paths. Thus, ANT should be
guided by the organization’s strategy.
Realized absorptive capacity. While the ability to acquire and assimilate external
knowledge may enable generation of a new, enlarged knowledge base, this will not
necessarily lead to superior performance (Brettel et al., 2011). Rather, external knowledge
must be translated into products and processes. Realized absorptive capacity is the
ability to leverage knowledge that has already been acquired and assimilated (Zahra and
George, 2002). It is comprised of transformation and exploitation.
Transformation. Transformation is the ability to combine existing knowledge with
newly acquired and assimilated knowledge (Zahra and George, 2002), adding, deleting
and interpreting it. Transformation changes the character of knowledge through the
combination of apparently incongruous sets of information to arrive at new insights,
facilitate recognition of opportunities and alter the way an organization sees itself and
its competitive landscape.
In ANT, transformation operates similarly, combining apparently incongruous sets
of information, with the goal of supporting future needs. Thus, transformation
includes the ability to understand potential technologies, the future environment and
the problems it anticipates facing.
Exploitation. According to the absorptive capacity literature, exploitation
applies knowledge to refine, extend and leverage existing competencies or create
new competencies by incorporating acquired and transformed knowledge (Zahra
and George, 2002). It is the ability to harvest external knowledge for commercial gain.
In terms of ANT, exploitation is the ability to apply transformed knowledge to
develop and implement new technologies in a way that supports future needs. It is
cumulative, so the more an organization has transferred knowledge into future
commercial applications in the past, the easier it is. Thus, past history of exploiting
external technology knowledge is an important component of ANT capability.
Relationship between ANT and supply chain management
We posit that supply chain management can support ANT through supply chain
planning, supplier integration and internal integration. The high-level focus of supply
chain planning helps in recognizing the potential need for new technologies in the
future. Further, the extent to which a supply chain is externally integrated (Bowersox
et al., 1999; Frohlich and Westbrook, 2001; Naylor et al., 1999) provides access to
external sources of knowledge about technology, while internal integration provides a
structure for assimilating external knowledge about new technologies.
Supply chain planning. Supply chain planning is important in developing a deep
understanding of the dynamic supply chain environment, in order to develop a
strategy for dealing with its challenges (Elbashir et al., 2011). A forward looking
perspective focusses on identifying gaps between current technology and what will be
needed to support future products, markets, environment and other challenges,
overseeing the transfer of technology between plants as needed and aligning the
capabilities of suppliers with current and future needs. In doing so, supply chain
planning focusses on suppliers as potential external sources of technology knowledge.
Internal integration. Internal integration, which is interaction and collaboration
between an organization’s internal functions (Kahn and Mentzer, 1998; Flynn et al.,
2010; Zhao et al., 2011), enhances knowledge exchange across internal functions by
bringing together different sources ( Jansen et al., 2005) to deepen knowledge flows
across functional boundaries and facilitate understanding of new external knowledge.
This enables employees to combine their existing and newly acquired knowledge,
providing the foundation for assimilation, transformation and exploitation. Without
effective internal integration, the potential of a new technology may not be recognized.
Supplier integration. A supply chain is an important external source of knowledge
about potential new technologies. A strong relationship with suppliers provides
fine-grained knowledge about their operations, personnel, resources (Uzzi, 1996;
Bernardes, 2010), blurring the boundaries between supply chain members and
increasing the efficiency of resource exchanges between them (Tsai and Ghoshal,
1998). Furthermore, linkages with suppliers’ extended networks (Mu et al., 2008)
may provide bridges to sources of unique external information (Tsai and Ghoshal,
1998) that trigger ideas that challenge existing knowledge and understanding. Thus,
supplier integration is important to the development of a rich network of diverse
knowledge ( Jansen et al., 2005) for transforming and exploiting new knowledge.
Figure 1 provides a summary of the hypotheses that were tested. The first set describes
our proposed antecedents to ANT.
Supply chain planning
Supply chain planning provides a foundation for effective supply chain integration and
ANT by driving a culture that focusses on future needs (Elbashir et al., 2011), aligning
future technology development with corporate strategy. It is important in developing
meaningful supplier integration, providing access to external knowledge from
customers, suppliers and their extended supply chain networks and developing
integrated internal structures for assimilating external information. Thus, supply
chain planning facilitates learning about potential new technologies through the
development of networks that facilitate the rapid flow of information:
H1a. Supply chain planning is positively related to internal integration.
H1b. Supply chain planning is positively related to supplier integration.
H1c. Supply chain planning is positively related to ANT.
Internal integration facilitates assimilation by providing a structure for absorbing
external knowledge. This is important because firm-specific external knowledge can
be difficult for a different organization to relate to. The ability to easily access-related
internal expertise facilitates evaluation of the relevance of external technological
advances (Cohen and Levinthal, 1990) to future needs. However, internal integration
can be challenging, due to what Bowersox et al. (1999) described as the “great
operating divide” (Bowersox et al., 1999) between the priorities, objectives and
terminology of operations-focussed ( procurement and manufacturing) and customer-
facing (logistics and marketing) activities. The operations-focussed side is driven by
the cost to provide goods, while the customer-facing side focusses on the cost to serve
customers. Thus, effective internal integration can be a means of competitive
H2a. Internal integration is positively related to supplier integration.
H2b. Internal integration is positively related to ANT.
Supplier relationships can provide novel perspectives about new technologies.
Overlap in knowledge with suppliers facilitates detailed, subject-specific interactions
(Azadegan, 2011), increasing awareness of supplier capabilities and making information
exchanges more efficient. Thus, ANT is enhanced by access to knowledge about new
technologies from suppliers and their extended networks:
H3. Supplier integration is positively associated with ANT.
The second set of hypotheses describes the relationship between ANT and performance.
Organizations that are skilled in ANT have the ability to pinpoint technologies
that will be needed in their future, while their less skilled competitors may blindly
pursue multiple investments and develop capabilities for a variety of new and mostly
irrelevant technologies. ANT is an important source of competitive advantage,
because it is valuable, rare, imperfectly imitable and non-substitutable (Barney, 2001;
Wernerfelt, 1984). Although current technology investments can be easily copied,
ANT’s focus on developing capabilities for aligning new technologies with future
needs provides a combination of hard and soft investments that is difficult to imitate.
While other organizations may have a substantial number of false starts down paths to
future technology, an organization that has capability in ANT has fewer; thus, ANT is
rare. In addition, relationships with suppliers and their extended networks leads to
development of a unique domain for the acquisition of external knowledge that is
inimitable. ANT is non-substitutable because it must be aligned with an organization’s
idiosyncratic history, environment and challenges; information from other sources
will not be as relevant. Because ANT is valuable, rare, imperfectly imitable and
non-substitutable, it is a potent source of competitive advantage. Thus:
H4. ANT is positively associated with performance.
H5. Supply chain planning is positively associated with performance.
Archival data from the high-performance manufacturing (HPM) project was used.
This data were collected from plants in ten countries and three industries. Table I
summarizes the sample characteristics.
Country Electronics Machinery Transportation components Total
Germany 9 13 19 41
Austria 10 7 4 21
China 21 16 14 51
South Korea 10 10 11 31
Spain 9 9 10 28
USA 9 11 9 29
Finland 14 6 10 30
Italy 10 10 7 27
Japan 10 12 13 35
Sweden 7 10 7 24
Total 109 104 104 317
Note: n, number of plants
Tabl e I.
HPM data set by
country and industry
The measurement instrument contained a mix of objective and subjective items on
topics related to manufacturing practices, compiled into questionnaires targeted at
different respondents. Each item was included on at least three questionnaires, in order
to improve validity. Within a given questionnaire, items with the same response
choices were intermingled, so that the underlying construct was not readily apparent.
The questionnaires were administrated by the plant research coordinator, a plant
employee who served as the liaison with the HPM project.
The measures are contained in Appendix. Supply chain planning, supplier integration,
internal integration and ANT were measured perceptually, using a seven-point
Likert scale, ranging from 1 ¼strongly disagree to 7 ¼strongly agree. Items relevant
to the role that supply chain planning potentially plays in ANT were selected from
items originally assigned to HPM measures entitled coordination of plant activities and
supply chain planning, which were administered to the inventory manager, three
supervisors and the plant superintendent. The items measuring internal integration
were originally assigned to HPM measures entitled functional integration and
integration between functions, administered to the process engineer, plant manager
and plant superintendent in each plant. The ANT measure was developed for the HPM
project based on Hayes and Wheelwright’s (1984) description and was administered
to a process engineer, the plant superintendent and plant manager. The supplier
integration measure used items from the HPM project’s supplier partnership measure,
and it was administered to ten direct labors, the inventory manager and quality manager.
Performance was measured using items from the HPM measure entitled competitive
performance, which were completed by the plant manager. He was asked to indicate how
the plant compared to its competition in the same industry, on a global basis, using
a five-point Likert measure, ranging from 1 ¼weak, among the worst in the industry to
5¼superior. Specifically, cost was operationalized as unit cost of manufacturing,
quality was operationalized as conformance to product specifications, delivery was
operationalized as on time delivery performance, flexibility was operationalized as
flexibility to change volume and innovation was operationalized as on-time new
Validity and reliability
Construct validity. Confirmatory factor analysis (CFA) was used to test the reliability
and validity of the measures. Items with a factor loading of at least 0.6 were included
(Chen and Paulraj, 2004), with a total of five items being excluded during formation of
the measures (see Table II). The exclusion of these items did not affect the underlying
meaning of the measure; for example, the item excluded from the supplier integration
measure focussed on the returns provided to the suppliers, rather than on a core
element of supplier integration. The included items had factor loadings between 0.6
and 0.83. All measures exceeded the acceptable minimum for Cronbach’s aof 0.60
(Hair et al., 2011), implying that they were internally consistent.
In the original operational performance measure, the item representing
cost performance had a factor loading of 0.39, below the criterion of 0.60. This is
not surprising, based on the tradeoffs literature (Skinner, 1969); improvements in a
dimension of operational performance often only come with increased investment.
Thus, cost was extracted from the operational performance measure and retained as an
independent, single item measure. The final operational performance measure was
a formative measure that included quality, delivery, flexibility and innovation performance.
Accordingly, H4 and H5 were modified to incorporate both endogenous variables,
H4a. ANT is positively related to operational performance (quality, delivery,
flexibility and innovativeness).
H4b. ANT is positively related to cost performance.
H5a. Supply chain planning is positively related to operational performance
(quality, delivery, flexibility and innovativeness).
H5b. Supply chain planning is positively related to cost performance.
Convergent validity. Convergent validity was verified by examining the item factor
loadings (Koufteros, 1999). Items with factor loadings less than 0.60 were deleted.
Table II shows the factor loadings for the retained items.
Discriminant validity. Discriminant validity was evaluated in two ways: the difference
(Bagozzi and Yi, 1988) and average variance extracted (AVE) (Fornell and Larcker,
1981). Table III contains the w
values for the constrained and unconstrained models.
Construct (a) Items Factor loading a
Anticipation of new technologies ANT1 0.65 0.806
Internal integration FI1 0.83 0.908
FI3 Excluded (0.54)
FI4 Excluded (0.53)
FI7 Excluded (0.48)
Supply chain planning SCP1 0.60 0.739
SCP2 Excluded (0.54)
Supplier integration SPT1 0.71 0.800
SPT2 Excluded (0.47)
Operational performance OP1 Extracted (0.39) 0.605
analysis and Cronbach’s a
All differences in w
between the models were significantly different, providing
evidence of discriminant validity. Table IV contains a summary of the AVE analysis.
Four of the constructs had an AVE above the criterion of 0.5, while supply chain
planning had an AVE of 0.46. This measure was retained because it was very close to
0.5 and because its composite reliability and convergent validity provided further
evidence of discriminant validity.
Composite reliability. Table IV contains the composite reliability values for the
measures. There is no general agreement on an acceptable level (Koufteros, 1999),
but values over 0.60 are considered desirable (Bagozzi and Yi, 1988). The composite
reliability for each of the measures was over 0.7.
The model was assessed using CFA (Chen and Paulraj, 2004). Its adequacy and
adjustment were assessed using adjusted goodness of fit, standardized RMR and
RMEA as standalone indices, normed fit index, incremental fit index, relative fit index,
comparative fit index and Tucker-Lewis coefficient as incremental indices and PNFI,
Akaike’s information criterion and CAIC for the default, saturated and independence
models as indices of parsimonious fit. The proposed relationships were simultaneously
verified using structural equation modeling (SEM), allowing analysis of the direct and
indirect relationships between the variables.
Construct pairs w
Anticipation of new technologies
Internal integration 50.376 34 151.319 35 100.943*
Supply chain planning 37.098 19 112.227 20 75.129*
Supplier integration 26.104 19 221.885 20 195.781*
Operational performance 48.639 19 215.171 20 166.532*
Supply chain planning
Internal integration 46.791 33 148.632 34 101.841*
Supplier integration 31.287 19 196.159 20 164.872*
Operational performance 49.936 19 208.230 20 158.294*
Internal integration 46.791 33 148.632 34 101.841*
Operational performance 48.186 19 307.712 20 259.526*
Operational performance 72.129 34 249.519 35 177.390*
Note: *po0.000 Table III.
Test of w
Constructs AVE Composite reliability
Anticipation of new technology 0.56 0.834
Supply chain planning 0.46 0.768
Supplier integration 0.70 0.903
Internal integration 0.74 0.944
Operational performance 0.55 0.788
Tabl e IV.
Table V presents the fit indices for the measurement model. All of the values were
acceptable, suggesting that the proposed model is acceptable. The means, standard
deviations and correlation coefficients between the exogenous variables are contained
in Table VI, which indicates that there is a significant positive relationship between all
Figure 2 contains the results of the analysis of the proposed path model, and
Table VII contains the goodness of fit indices. All were acceptable, indicating that the
proposed path model is a good fit to the data. Table VIII presents the estimated
coefficients and their statistical significance. Table IX contains the results of the
The first set of hypotheses focussed on the antecedents to ANT. The coefficients for
the paths from supply chain planning to both internal and supplier integration were
Index Value Criterion
Degrees of freedom (df) 197
Probability level 0.086
Goodness of fit (GFI) 0.941 40.9
Adjusted goodness of fit (AGFI) 0.924 40.9
Standardized RMR 0.027 Close to 0
RMSEA 0.021 o0.05
Normed fit index (NFI) 0.927 40.9
Incremental fit index (IFI) 0.990 40.9
Relative fit index (RFI) 0.915 40.9
Comparative fit index (CFI) 0.990 40.9
Tucker-Lewis coefficient (TLI) 0.989 40.9
Indices of parsimonious fit
PNFI 0.791 40.5
Akaike’s information criterion (AIC) AIC CAIC
Default model 336.610 603.109 Smallest value must be the proposed
Saturated model 506.000 1,710.002
Independence model 3,127.231 3,231.927
Tabl e V.
Fit indices for the
planning 317 4.9203 0.69070 0.391
Internal integration 317 5.3173 0.63906 0.352
Supplier integration 317 5.2541 0.53161 0.393
Anticipation of new
technologies 317 5.1698 0.75648 0.449
performance 317 3.8347 0.56100
Descriptive statistics and
positive and statistically significant, supporting H1a and H1b. Organizations with
stronger supply chain planning also had stronger internal integration and ANT.
Similarly, H2a and H2b were supported. This indicates that supplier integration and
ANT were stronger in the presence of internal integration. Supplier integration had
supply chain planning and internal integration as its antecedents. The coefficient for
H3 was positive and statistically significant, thus, supplier integration is related to
Notes: SCPL, supply chain planning; SUINT, supplier integration; INT, internal integration;
ANT, anticipation of new technology; OP, operational performance (quality, delivery,
flexibility and innovation); CP, cost performance
Index Value Criterion
Degrees of freedom (df) 4
Probability level 0.098
Goodness of fit (GFI) 0.994 40.9
Adjusted goodness of fit (AGFI) 0.967 40.9
Standardized RMR 0.009 Close to 0
RMSEA 0.040 o0.05
Normed fit index (NFI) 0.985 40.9
Incremental fit index (IFI) 0.995 40.9
Relative fit index (RFI) 0.945 40.9
Comparative fit index (CFI) 0.995 40.9
Tucker-Lewis coefficient (TLI) 0.981 40.9
Indices of parsimonious fit
PNFI 0.263 40.5
Akaike’s information criterion AIC CAIC Smallest value must be the proposed
Default model 40.025 120.926
Saturated model 42.000 141.937
Independence model 425.992 454.545
Path analysis fit indices
ANT. Combined, the results of the tests of H1-H3 indicate that supply chain planning,
internal integration and supplier integration are all antecedents of ANT.
The second set of hypothesis tests focussed on competitive performance. The
coefficients for H4a and H4b were both statistically significant and positive, indicating
that ANTwas positively related to both operational performance and cost performance.
The significant coefficient for H5a shows that supply chain planning is related to
operational performance. The coefficient for H5b was not statistically significant, thus,
there was not a direct relationship between supply chain planning and cost performance.
Table IX indicates that there were a number of significant indirect effects. The total
effect of supply chain planning was strongest for its relationship with ANT (0.348).
Similarly, the strongest total effects of supplier integration (0.207) and internal
integration (0.487) were with ANT. Although supply chain planning was not directly
related to cost performance, it was indirectly related through its relationship to ANT.
This is consistent with the notion that supply chain planning lays for foundation for
supply chain integration, which enhances an organization’s ability to anticipate new
Hypothesis Proposed Path Coefficient p
H1a Supply chain planning-internal integration 0.362 0.001
H1b Supply chain planning-supplier Integration 0.286 0.001
H1c Supply chain planning-anticipation of new technologies 0.275 0.001
H2a Internal integration-supplier integration 0.172 0.001
H2b Internal integration-anticipation of new technologies 0.452 0.001
H3 Supplier integration-anticipation of new technologies 0.207 0.004
H4a Anticipation of new technologies-operational performance 0.262 0.001
H4b Anticipation of new technologies-cost performance 0.251 0.001
H5a Supply chain planning-operational performance 0.140 0.001
H5b Supply chain planning-cost performance 0.103 0.171
Summary of the SEM
test for the model
Direct Indirect Total
Effect of supply chain planning
Supplier integration 0.286 0.062 0.348
Internal integration 0.362 – 0.362
Anticipation of new technologies 0.140 0.164 0.304
Operational performance 0.103 (ns) 0.134 0.237
Cost performance 0.100 0.128 0.228
Effect of supplier integration
Anticipation of new technologies 0.207 – 0.207
Operational performance – 0.054 0.054
Cost performance – 0.052 0.052
Effect of internal integration
Supplier integration 0.172 – 0.172
Anticipation of new technologies 0.452 0.035 0.487
Operational performance – 0.127 0.127
Cost performance – 0.122 0.122
Effect of anticipation of new technologies
Operational performance 0.262 – 0.262
Cost performance 0.251 – 0.251
Direct and indirect
This research examined the antecedents to ANT, as well as its relationship to operational
and cost performance. It found that supply chain planning, internal integration and
supplier integration were all associated with ANT, and that it was associated with
both operational and cost performance. Furthermore, supply chain planning, internal
integration and supplier integration were indirectly related to operational and cost
performance, through ANT. The strongest total relationship was between internal
integration and ANT. We propose that this is because an organization that has its own
house in order internally has a structure for assimilating and transforming external
knowledge, which provides important inputs about technology decisions for future
generations of products. The total effect of supply chain planning on ANT was the next
strongest. While this was partly due to the total effect of internal integration on ANT,
it nonetheless demonstrates the importance of supply chain planning on ANT.
Thus, through the direct and indirect effects found, this study provides compelling
evidence for the importance of supply chain management in supporting ANT.
This research makes several contributions to the literature. First, it provides
a reliable and valid measure of ANT. Although this construct was introduced by Hayes
and Wheelwright (1984), who discussed its importance, having a reliable and valid
measure of ANT provides a foundation for researchers to continue to learn more about
this construct. Using CFA, we established the reliability and construct, convergent,
discriminant and composite validity of this measure, showing that our measure of
ANT is appropriate for future empirical research.
Second, this research provides insights into its infrastructure and effects, by
testing ANT in a model that included antecedents and performance measures.
We found that organizations that were stronger in ANT had better operations and
cost performance. This is consistent with the predictions of Hayes and Wheelwright
(1984), proving empirical support for their conceptual description of this construct
and its expected effects.
Third, and perhaps most interesting, is that we found that elements of supply chain
management were antecedents to ANT. In this sense, we move beyond the conceptual
work of Hayes and Wheelwright (1984), who focussed primarily on the expected
performance effects of ANT. Although they viewed ANT as a characteristic of world
class manufacturers, they put less emphasis on the infrastructure that fosters its
development. We found that supply chain planning, supplier integration and internal
integration were positively related to ANT; thus, organizations that have stronger
supply chain planning, supplier integration and internal integration also had higher
levels of ANT. We built upon social capital theory to consider how suppliers’ ties
with their external networks of customers and suppliers provide access to external
knowledge about new technologies and future customer needs that might not
otherwise be available. This puts ANT in a different light, placing it in the realm of
supply chain management research, as well as operations strategy research.
Fourth, we positioned ANT in the theoretical literature on absorptive capacity,
examining Hayes and Wheelwright’s (1984) experience-based insights through the lens
of well established theory. Understanding the role of supply chain management is
important in this positioning, since it provides a means of enhancing the absorptive
capacity that underlies ANT. We propose that focussing on technologies that may be
important in the future provides the impetus for environmental scanning to accelerate
knowledge acquisition, and suppliers and their external networks are critical sources
of external knowledge. Internal integration provides a structure for analyzing,
processing, interpreting and developing an understanding of external knowledge,
supporting assimilation. Similarly, supply chain planning and internal integration are
important in transformation and exploitation of external knowledge about technology
that may be important in the future. This positioning in the theoretical literature is
important in understanding ANT and providing a foundation for future research on
this important construct. Although we described ANT in the context of absorptive
capacity, we did not test any absorptive capacity constructs; this is a fruitful area for
future research. Thus, by positioning ANT in the theoretical literature, we hope that
we have revitalized the discussion of a well-respected established construct that has
not benefitted from prior empirical testing.
This research is relevant in today’s dynamic global environment, despite
being based on a construct that was proposed almost 30 years ago. In the face of
a rapidly changing competitive environment, ANT has the potential to be a powerful
competitive weapon to give an organization an edge over its competitors which, like
Company A, remain focussed on using today’s technologies to address today’s problems.
Although this may be a very effective short-term strategy, it does not position an
organization well for dealing with a changing environment. Furthermore, today’s global
extended supply chains provide a potential treasure trove of knowledge about
technology for organizations that recognize and capitalize on it. Testing the role of ANT
in a dynamic environment provides an important opportunity for future research.
In addition to its contribution to the theoretical literature, this research has strong
managerial implications. It is based on Hayes and Wheelwright’s (1984) work with
companies and managers, so its roots are inherently practical. By shedding new light on an
old construct, we hope to provide a reminder of the importance of focussing on future
customer needs and the technology and capabilities to support them, in order to develop
them in advance of actual need. Second, this research shows that Hayes and Wheelwright’s
(1984) practical prescriptions are valid. The association between ANT and operational
performance shows the importance of a technology strategy that looks to the future,
as well as the present. Although it is important to stay current with competitors in terms of
technology, this is the road to competitive parity, as illustrated Company A. Because
state-of-the-art process and manufacturing technology is available to any organization that
has the resources to invest in it, only keeping up with technology does not provide a source
of competitive differentiation. Thus, to achieve a competitive advantage, future, as well as
current, technology needs should be considered, as illustrated by Company B.
Third, we highlight the importance of supply chain management practices in fostering
ANT. By viewing supply chain partners and their partners as a source of important
technology knowledge and developing a means for systematically capturing this
knowledge, processing it and capitalizing on it, ANT is enhanced. This also supports the
notion of world class manufacturing as building upon linkages between many diverse
practices. Relationships with suppliers are enhanced by strong internal integration,
providing the ability to use knowledge acquired externally. When the operations-facing
and customer-facing sides of an organization speak the same language and work together
to collaboratively achieve goals, supplier integration is facilitated. A strong internal
structure facilitates development of understanding so that external knowledge can be
applied to the organization’s unique problems and improve its operational performance.
Future directions and limitations
While Hayes and Wheelwright’s (1984) work is rich with managerial implications,
it has not, for the most part, been subject to empirical scrutiny. ANT is one of their
three “acid tests” for being a world class (stage 4) manufacturer. The other two
acid tests are the extent to which an organization develops its own proprietary
equipment and the extent of integration between structural and infrastructural
decisions. There are many important research questions based on the three acid
tests, including whether they are, indeed, the key differentiators between the best
manufacturers in the world and the others. Do they interact with each other and,
if so, how? Is there a common infrastructure that supports their development?
By developing a reliable and valid measure for one of Hayes and Wheelwright’s
(1984) acid tests, we have contributed to this discussion, but this is only the
On a broader level, ANT is an element of world class manufacturing, but there are
numerous important research questions about its other elements, their relationship
with each other and their relationship with performance. In particular, it is likely that
there are other important antecedents to ANT, beyond the supply chain management
factors examined in this research. ANT may also interact with other elements of world
class manufacturing in its influence on performance.
Part of what makes research on world class manufacturing so challenging is that
its components may be implemented differently in different national cultures.
For example, the long-term orientation (Hofstede, 2001) of a national culture may be
important in its orientation toward ANT. Examining the relationship between long-term
orientation and ANT may be insightful. Further, it is important to consider potential
substitutes for long-term orientation; in a national culture with a shorter-term focus,
are there alternative ways to lay a foundation for ANT?
As with all empirical research, there are a number of potential limitations that
should be articulated. The use of an existing database like the HPM database can be
restrictive in terms of the research questions that can be investigated. In this study,
however, the HPM database included measures relevant to ANT and supply chain
integration. Thus, the content of the database led to few restrictions on the research
ideas and questions proposed.
Focussing on the plant as the unit of analysis may have limited conclusions
regarding performance and the impact of ANT. This leads to several opportunities for
future research. First, it is important to consider the corporate perspective of ANT,
which may provide valuable insights into how future products, markets and strategic
needs are envisioned, as well as how that vision is communicated to the plant level.
Second, consideration of supply chain integration that includes the perspectives of
customers and suppliers, as well as the focal organization, will enrich future studies
of the role that supply chain management plays in ANT.
This study focussed only on suppliers as a supply chain source of new technology
knowledge. However, customers may also be a potent source of new technology knowledge.
Like suppliers, customers have their own extended networks of customers and suppliers
that can provide access to different sources of knowledge about technologies that align with
anticipated future needs. Future studies of ANT should include customer integration,
as well as supplier integration.
Anticipation of technologies is an important strategic construct that has not
benefitted from prior empirical study. This study lays the foundation for future
research on this topic through the establishment of a reliable and valid measure
and examination of its supply chain management antecedents. There are many
opportunities for further development and understanding of this construct through
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About the authors
Dr Andrew Beheregarai Finger is an Associate Professor at the Universidade Federal de Alagoas
(UFAL). He received his PhD from the Unisinos in Brazil. His research interests are global supply
chain, international operations and sustainable operations. He teaches courses in general
management, operations management, strategic alliances and sustainability.
Dr Barbara B. Flynn is the Richard M. and Myra Louise Buskirk Professor of the
Manufacturing Management in the Kelley School of Business, Indiana University. She is
Please indicate the extent to which you agree with each of the following statements (1 ¼strongly
disagree, 7 ¼strongly agree)
II1 The functions in our plant are well integrated
II2 Problems between functions are solved easily, in this plant
II3 Functional coordination works well in our plant (Excluded).
II4 Our business strategy is implemented without conflicts between functions (Excluded)
II5 The functions in our plant work well together
II6 The functions in our plant cooperate to solve conflicts between them, when they arise
II7 The marketing and finance areas know a great deal about manufacturing (Excluded)
II8 Our plant’s functions coordinate their activities
II9 Our plant’s functions work interactively with each other
Supply chain planning
SCP1 Our corporation implements ordering and stock management policies, on a global measure,
in order to coordinate distribution
SCP2 Our corporation performs aggregate planning for plants, according to our global
distribution needs (Excluded)
SCP3 Our corporation transfers technological innovations and know-how between plants
SCP4 We actively plan supply chain activities
SCP5 We monitor the performance of members of our supply chains, in order to adjust supply
Anticipation of new technologies
ANT1 We pursue long-range programs, in order to acquire manufacturing capabilities in advance
of our needs
ANT2 We make an effort to anticipate the potential of new manufacturing practices and
ANT3 Our plant stays on the leading edge of new technology in our industry
ANT4 We are constantly thinking of the next generation of manufacturing technology
SPT1 We maintain cooperative relationships with our suppliers
SPT2 We provide a fair return to our suppliers (Excluded)
SPT3 We help our suppliers to improve their quality
SPT4 We maintain close communications with suppliers about quality considerations and design
SPT5 Our key suppliers provide input into our product development projects
Please indicate the performance of your plant, compared with its global competitors (1 ¼weak, among
the worst in the industry, 5 ¼superior)
OP1 Unit cost of manufacturing (Extracted)
OP2 Conformance to product specifications
OP3 On time delivery performance
OP4 Flexibility to change volume
OP5 On time new product launch
the author of two research books and numerous publications related to supply chain
management, operations strategy, quality management and other topics in top journals.
The recipient of over $1 million in research funding from the National Science Foundation, the US
Department of Education and the Center for Innovation Management Studies, she is the past
President of the Decision Sciences Institute, as well as Fellow and recipient of the Dennis E.
Grawoig Distinguished Service Award. Professor Flynn is the past Editor-In Chief of Quality
Management Journal and Founding Editor of Decision Sciences Journal of Innovative Education.
She teaches courses in operations and supply chain management, project management and
service operations management. She is the past Director of the Indiana University Center for
International Business Education and Research. Dr Barbara B. Flynn is the corresponding author
and can be contacted at: email@example.com
Dr Ely Laureanos Paiva is an Associate Professor at the Fundacao Getulio Vargas (FGV) in
Sao Paulo, Brazil. He was Visiting Scholar at the University of North Carolina, Chapel Hill and at
the University of Texas Pan American. He has published in journals like Journal of Operations
Management,Journal of Cleaner Production,Journal of Knowledge Management,International
Journal of Service and Operations Management and Industrial Management & Data Systems.
His current research project is funded by the Brazilian Research National Agency (CNPq ) and
the Research Agency from the State of Sao Paulo (FAPESP). He is an Editor-in-Chief of the
Journal of Operations and Supply Chain Management. Professor Paiva is the Associate Dean of
the Doctoral Program of the Fundacao Getulio Vargas (FGV) in Sao Paulo.
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